{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T17:05:38Z","timestamp":1779728738195,"version":"3.53.1"},"reference-count":262,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers and Electronics in Agriculture"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.compag.2026.111785","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:24:59Z","timestamp":1776810299000},"page":"111785","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Non-contact technologies for cattle monitoring: advances and challenges towards precision livestock farming"],"prefix":"10.1016","volume":"248","author":[{"given":"Xingshi","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benhai","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomas","family":"Norton","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4508-5338","authenticated-orcid":false,"given":"Huaibo","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compag.2026.111785_b0005","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.biosystemseng.2020.07.019","article-title":"Image analysis for individual identification and feeding behaviour monitoring of dairy cows based on Convolutional Neural Networks (CNN)","volume":"198","author":"Achour","year":"2020","journal-title":"Biosyst. Eng."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0010","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.livsci.2007.04.010","article-title":"Live weight, body size and carcass characteristics of young bulls of fifteen European breeds","volume":"114","author":"Albert\u00ed","year":"2008","journal-title":"Livest. Sci."},{"issue":"1\u20133","key":"10.1016\/j.compag.2026.111785_b0015","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.livsci.2007.08.018","article-title":"Evaluation of retinal imaging technology for the identification of bovine animals in Northern Ireland","volume":"116","author":"Allen","year":"2008","journal-title":"Livest. Sci."},{"key":"10.1016\/j.compag.2026.111785_b0020","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.compag.2018.09.039","article-title":"Body condition estimation on cows from depth images using Convolutional Neural Networks","volume":"155","author":"Alvarez","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0025","doi-asserted-by":"crossref","unstructured":"Awad, A., Zawbaa, H., Mahmoud, H., Nabi, E., Fayed, R., Hassanien, A. (2013). A robust cattle identification scheme using muzzle print images. Federated conference on computer science and information systems (FedCSIS), Krakow, POLAND.","DOI":"10.1007\/978-3-642-40597-6_12"},{"key":"10.1016\/j.compag.2026.111785_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109976","article-title":"Cattle weight estimation model through readily photos","volume":"143","author":"Bai","year":"2025","journal-title":"Eng. Appl. Artif. Intel."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0035","doi-asserted-by":"crossref","DOI":"10.1109\/JIOT.2023.3294944","article-title":"An intelligence cattle re-identification system over transport by siamese neural networks and YOLO","volume":"11","author":"Bakhshayeshi","year":"2023","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.compag.2026.111785_b0040","doi-asserted-by":"crossref","unstructured":"Bao, Y., Lu, H., Wu, J., Lei, J., Zhang, J., Lou, X., Guo, H., 2023. Rapid and automated body measurement of cattle based on statistical shape model. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. X-1\/W1-2023, 541-546.","DOI":"10.5194\/isprs-annals-X-1-W1-2023-541-2023"},{"key":"10.1016\/j.compag.2026.111785_b0045","article-title":"Lightweight pruning-driven YOLOv8-PMP for visual detection of pine nut rot","volume":"13","author":"Bao","year":"2026","journal-title":"Smart Agric. Technol."},{"issue":"5","key":"10.1016\/j.compag.2026.111785_b0050","doi-asserted-by":"crossref","first-page":"8984","DOI":"10.48048\/wjst.2021.8984","article-title":"Deep belief network approach for recognition of cow using cow nose image pattern","volume":"18","author":"Bello","year":"2021","journal-title":"Walailak Journal of Science and Technology (WJST)."},{"key":"10.1016\/j.compag.2026.111785_b0055","series-title":"Multi-Views Embedding for Cattle Re-Identification","author":"Bergamini","year":"2018"},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.animal.2024.101079","article-title":"Biometric identification of dairy cows via real-time facial recognition","volume":"18","author":"Bergman","year":"2024","journal-title":"Animal"},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0065","doi-asserted-by":"crossref","first-page":"3439","DOI":"10.3168\/jds.2007-0836","article-title":"Potential for estimation of body condition scores in dairy cattle from digital images","volume":"91","author":"Bewley","year":"2008","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.116354","article-title":"CORF3D contour maps with application to Holstein cattle recognition from RGB and thermal images","volume":"192","author":"Bhole","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109718","article-title":"A systematic survey of public computer vision datasets for precision livestock farming","volume":"229","author":"Bhujel","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"6","key":"10.1016\/j.compag.2026.111785_b0080","doi-asserted-by":"crossref","first-page":"3564","DOI":"10.3168\/jds.2012-5597","article-title":"Associations between locomotion score and kinematic measures in dairy cows with varying hoof lesion types","volume":"96","author":"Blackie","year":"2013","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.111404","article-title":"Automated detection and localization of hoof diseases in dairy cattle using an integrated computer vision and infrared thermography system","volume":"243","author":"Bumb\u00e1lek","year":"2026","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107586","article-title":"Application and research progress of infrared thermography in temperature measurement of livestock and poultry animals: a review","volume":"205","author":"Cai","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0095","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.compag.2008.05.014","article-title":"Automatic real-time monitoring of locomotion and posture behaviour of pregnant cows prior to calving using online image analysis","volume":"64","author":"Cangar","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0100","doi-asserted-by":"crossref","unstructured":"Chen, S., Ge, C., Tong, Z., Wang, J., Song, Y., Wang, J., Luo, P. 2022. AdaptFormer: Adapting vision transformers for scalable visual recognition. arXiv preprint arXiv:2205.13535.","DOI":"10.52202\/068431-1212"},{"key":"10.1016\/j.compag.2026.111785_b0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.jtherbio.2025.104154","article-title":"Respiratory rate detection of dairy cows based on infrared thermography in head movement scenarios","volume":"130","author":"Chen","year":"2025","journal-title":"J. Therm. Biol"},{"key":"10.1016\/j.compag.2026.111785_b0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.iot.2025.101674","article-title":"IoT-based system for individual dairy cow feeding behavior monitoring using cow face recognition and edge computing","volume":"33","author":"Chen","year":"2025","journal-title":"Internet Things"},{"issue":"12","key":"10.1016\/j.compag.2026.111785_b0115","doi-asserted-by":"crossref","first-page":"10558","DOI":"10.1109\/TPAMI.2024.3447085","article-title":"A survey on deep neural network pruning: taxonomy, comparison, analysis, and recommendations","volume":"46","author":"Cheng","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0120","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1017\/S002202991200060X","article-title":"Predisposing factors for involuntary culling in Holstein\u2013Friesian dairy cows","volume":"80","author":"Chiumia","year":"2012","journal-title":"J. Dairy Res."},{"key":"10.1016\/j.compag.2026.111785_b0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108131","article-title":"Fusion of udder temperature and size features for the automatic detection of dairy cow mastitis using deep learning","volume":"212","author":"Chu","year":"2023","journal-title":"Comput. Electron. Agric."},{"issue":"11","key":"10.1016\/j.compag.2026.111785_b0130","first-page":"1","article-title":"Researchadvancesintheautomaticdetectiontechnology formastitisofdairycows","volume":"39","author":"Chu","year":"2023","journal-title":"Transactions of the Chinese Society of Agricultural Engineering."},{"key":"10.1016\/j.compag.2026.111785_b0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110937","article-title":"Multi-feature image layers fusion for accurate detection of dairy cow mastitis using deep learning","volume":"239","author":"Chu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0140","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.biosystemseng.2023.10.001","article-title":"Subcutaneous temperature monitoring through ear tag for heat stress detection in dairy cows","volume":"235","author":"Chung","year":"2023","journal-title":"Biosyst. Eng."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0145","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.rvsc.2013.11.006","article-title":"Influence of environmental factors on infrared eye temperature measurements in cattle","volume":"96","author":"Church","year":"2014","journal-title":"Res. Vet. Sci."},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b0150","first-page":"425","article-title":"U-net-based approaches for biometric identification and recognition in cattle","volume":"31","author":"C\u00edhan","year":"2025","journal-title":"Kafkas Universitesi Veteriner Fakultesi Dergisi."},{"key":"10.1016\/j.compag.2026.111785_bib1306","doi-asserted-by":"crossref","unstructured":"Cihan, P., Sayg\u0131l\u0131, A., Ermutlu, C. \u015e., Aky\u00fczl\u00fc, M., Ayd\u0131n, U., Y\u0131lmaz, A., \u00d6zmen, N. E., Aksoy, \u00d6., 2025b. U-Net-based approaches for biometric identification and recognition in cattle. Kafkas Univ. Vet. Fak. Derg. 31(3), 10.9775\/kvfd.2025.34130.","DOI":"10.9775\/kvfd.2025.34130"},{"key":"10.1016\/j.compag.2026.111785_b0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109391","article-title":"AI-aided cardiovascular disease diagnosis in cattle from retinal images: machine learning vs. deep learning models","volume":"226","author":"Cihan","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0160","doi-asserted-by":"crossref","DOI":"10.1016\/j.livsci.2019.103904","article-title":"Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases","volume":"232","author":"Cominotte","year":"2020","journal-title":"Livest. Sci."},{"key":"10.1016\/j.compag.2026.111785_b0165","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110987","article-title":"Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions","volume":"239","author":"Curti","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2019.105019","article-title":"Methodology for data processing and analysis techniques of infrared video thermography used to measure cattle temperature in real time","volume":"167","author":"Cuthbertson","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0175","doi-asserted-by":"crossref","first-page":"987","DOI":"10.2147\/IDR.S295257","article-title":"Prevalence and risk factors of mastitis and isolation, identification and antibiogram of staphylococcus species from mastitis positive zebu cows in toke kutaye, cheliya, and dendi districts, west shewa zone, oromia, ethiopia","volume":"14","author":"Dabele","year":"2021","journal-title":"Infect. Drug Resist."},{"issue":"11","key":"10.1016\/j.compag.2026.111785_b0180","doi-asserted-by":"crossref","first-page":"10142","DOI":"10.3168\/jds.2018-14619","article-title":"Epidemiologic and economic analyses of pregnancy loss attributable to mastitis in primiparous Holstein cows","volume":"101","author":"Dahl","year":"2018","journal-title":"J. Dairy Sci."},{"issue":"1\u20132","key":"10.1016\/j.compag.2026.111785_b0185","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/S0167-5877(01)00176-3","article-title":"Detection model for mastitis in cows milked in an automatic milking system","volume":"49","author":"de Mol","year":"2001","journal-title":"Prev. Vet. Med."},{"issue":"10","key":"10.1016\/j.compag.2026.111785_b0190","doi-asserted-by":"crossref","first-page":"3876","DOI":"10.3168\/jds.S0022-0302(06)72430-4","article-title":"Economic value of pregnancy in dairy cattle","volume":"89","author":"de Vires","year":"2006","journal-title":"J. Dairy Sci."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0195","doi-asserted-by":"crossref","first-page":"s155","DOI":"10.1017\/S1751731119003264","article-title":"Review: Overview of factors affecting productive lifespan of dairy cows","volume":"14","author":"De Vries","year":"2020","journal-title":"Animal"},{"key":"10.1016\/j.compag.2026.111785_b0200","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110103","article-title":"Fusion of CREStereo and MobileViT-Pose for rapid measurement of cattle body size","volume":"232","author":"Deng","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0205","doi-asserted-by":"crossref","unstructured":"Denis-Robichaud, J., Kelton, D., Fauteux, Villettaz-Robichaud, M., Dubuc, J., 2020. Short communication: Accuracy of estimation of lameness, injury, and cleanliness prevalence by dairy farmers and veterinarians. J. Dairy Sci. 103(11), 10696-10702.","DOI":"10.3168\/jds.2020-18651"},{"key":"10.1016\/j.compag.2026.111785_b0210","article-title":"Deep learning aided computer vision system forautomated linear type trait evaluation indairy cows","volume":"8","author":"Devi","year":"2024","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.compag.2026.111785_b0215","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.biosystemseng.2021.02.001","article-title":"Image-based body mass prediction of heifers using deep neural networks","volume":"204","author":"Dohmen","year":"2021","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107059","article-title":"Automatic livestock body measurement based on keypoint detection with multiple depth cameras","volume":"198","author":"Du","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"10","key":"10.1016\/j.compag.2026.111785_b0225","doi-asserted-by":"crossref","first-page":"3833","DOI":"10.3168\/jds.S0022-0302(06)72425-0","article-title":"Body condition assessment using digital images","volume":"89","author":"Ferguson","year":"2006","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0230","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107272","article-title":"Using dorsal surface for individual identification of dairy calves through 3D deep learning algorithms","volume":"201","author":"Ferreira","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0235","doi-asserted-by":"crossref","first-page":"3166","DOI":"10.3168\/jds.S0022-0302(05)73000-9","article-title":"Hoof pathologies influence kinematic measures of dairy cow gait","volume":"88","author":"Flower","year":"2005","journal-title":"J. Dairy Sci."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0240","doi-asserted-by":"crossref","first-page":"201","DOI":"10.4025\/actascianimsci.v39i2.33118","article-title":"Evaluation of body weight prediction Equations in growing heifers","volume":"39","author":"Franco","year":"2017","journal-title":"Acta Scientiarum. Animal Sciences."},{"key":"10.1016\/j.compag.2026.111785_b0245","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105627","article-title":"Deep learning-based hierarchical cattle behavior recognition with spatio- temporal information","volume":"177","author":"Fuentes","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108906","article-title":"Udder thermogram-based deep learning approach for mastitis detection in Murrah buffaloes","volume":"220","author":"Gayathri","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.rvsc.2025.105899","article-title":"Deep learning enhanced thermographic modeling for early and precise mastitis detection in Sahiwal cows","volume":"196","author":"Gayathri","year":"2025","journal-title":"Res. Vet. Sci."},{"key":"10.1016\/j.compag.2026.111785_b0260","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109399","article-title":"Motion focus global-local network: Combining attention mechanism with micro action features for cow behavior recognition","volume":"226","author":"Geng","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0265","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.compag.2013.08.012","article-title":"Automatic assessment of dairy cattle body condition score using thermal imaging","volume":"99","author":"Halachmi","year":"2013","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0270","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110301","article-title":"Utilizing farm knowledge for indoor precision livestock farming: Time-domain adaptation of cattle face recognition","volume":"234","author":"Han","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0275","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110059","article-title":"ASGP-IDet: Temporal behaviour localisation of beef cattle in untrimmed surveillance videos","volume":"232","author":"Han","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b0280","first-page":"203","article-title":"Novel method for the recognition of Jinnan cattle action using bottleneck attention enhanced two-stream neural network","volume":"17","author":"Hao","year":"2024","journal-title":"Int. J. Agric. Biol. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0285","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120551","article-title":"A novel Jinnan individual cattle recognition approach based on mutual attention scheme","volume":"230","author":"Hao","year":"2023","journal-title":"Expert Syst. Appl."},{"issue":"12","key":"10.1016\/j.compag.2026.111785_b0290","doi-asserted-by":"crossref","first-page":"3576","DOI":"10.3168\/jds.S0022-0302(92)78134-X","article-title":"Predicting body-weight and wither height in holstein heifers using body measurements","volume":"75","author":"Heinrichs","year":"1992","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0295","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108573","article-title":"Leveraging computer vision-based pose estimation technique in dairy cows for objective mobility analysis and scoring system","volume":"217","author":"Higaki","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0300","first-page":"138","article-title":"A systematic review of machine learning techniques for cattle identification: Datasets, methods and future directions","volume":"6","author":"Hossain","year":"2022","journal-title":"Artif. Intell. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0305","article-title":"Artificial intelligence in veterinary and animal science: applications, challenges, and future prospects","volume":"235","author":"Hossein-Zadeh","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0310","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108184","article-title":"Body weight estimation of beef cattle with 3D deep learning model: PointNet++","volume":"213","author":"Hou","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0315","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110013","article-title":"CattlePartNet: an identification approach for key region of body size and its application on body measurement of beef cattle","volume":"232","author":"Hou","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0320","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.biosystemseng.2020.02.001","article-title":"Cow identification based on fusion of deep parts features","volume":"192","author":"Hu","year":"2020","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0325","doi-asserted-by":"crossref","DOI":"10.3389\/fgene.2021.695543","article-title":"Analysis of Longevity Traits in Holstein cattle: a Review","volume":"12","author":"Hu","year":"2021","journal-title":"Front. Genet."},{"key":"10.1016\/j.compag.2026.111785_b0330","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110456","article-title":"AngusRecNet: Multi-module cooperation for facial anti-occlusion recognition in single-stage Angus cattle","volume":"236","author":"Hu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0335","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108152","article-title":"An effective PoseC3D model for typical action recognition of dairy cows based on skeleton features","volume":"212","author":"Hua","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0340","first-page":"4131","article-title":"Feature representation learning for calving detection of cows using video frames","author":"Hyodo","year":"2020","journal-title":"International Conference on Pattern Recognition."},{"key":"10.1016\/j.compag.2026.111785_b0345","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.biosystemseng.2016.09.017","article-title":"Early and non-intrusive lameness detection in dairy cows using 3-dimensional video","volume":"153","author":"Jabbar","year":"2017","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0350","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.applanim.2012.04.002","article-title":"Behaviour around the time of calving in dairy cows","volume":"139","author":"Jensen","year":"2012","journal-title":"Appl. Anim. Behav. Sci."},{"key":"10.1016\/j.compag.2026.111785_b0355","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106729","article-title":"Dairy cow lameness detection using a back curvature feature","volume":"194","author":"Jiang","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0360","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105536","article-title":"Single-stream long-term optical flow convolution network for action recognition of lameness dairy cow","volume":"175","author":"Jiang","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0365","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.biosystemseng.2024.12.009","article-title":"In situ volume measurement of dairy cattle via neural radiance fields-based 3D reconstruction","volume":"250","author":"Jing","year":"2025","journal-title":"Biosyst. Eng."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0370","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.3168\/jds.2017-14345","article-title":"Evaluation of 3 esterase tests for the diagnosis of subclinical mastitis at dry-off and freshening in dairy cattle","volume":"102","author":"Kandeel","year":"2019","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0375","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106922","article-title":"Dimension-reduced spatiotemporal network for lameness detection in dairy cows","volume":"197","author":"Kang","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0380","doi-asserted-by":"crossref","first-page":"429","DOI":"10.3758\/BF03195520","article-title":"Infrared imaging technology and biological applications","volume":"35","author":"Kastberger","year":"2003","journal-title":"Behav. Res. Methods Instrum. Comput."},{"issue":"10","key":"10.1016\/j.compag.2026.111785_b0385","doi-asserted-by":"crossref","first-page":"4771","DOI":"10.1007\/s00500-022-06935-x","article-title":"Cattle identification with muzzle pattern using computer vision technology: a critical review and prospective","volume":"26","author":"Kaur","year":"2022","journal-title":"Soft. Comput."},{"issue":"6","key":"10.1016\/j.compag.2026.111785_b0390","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1136\/vr.163.6.175","article-title":"Animal-based measurements of the severity of mastitis in dairy cows","volume":"163","author":"Kemp","year":"2008","journal-title":"Vet. Rec."},{"issue":"3\u20134","key":"10.1016\/j.compag.2026.111785_b0395","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.applanim.2003.12.001","article-title":"A proposition for an updated behavioural characterisation of the oestrus period in dairy cows","volume":"87","author":"Kerbrat","year":"2004","journal-title":"Appl. Anim. Behav. Sci."},{"issue":"13","key":"10.1016\/j.compag.2026.111785_b0400","doi-asserted-by":"crossref","first-page":"6621","DOI":"10.3390\/app12136621","article-title":"Development of an algorithm for rapid herd evaluation and predicting milk yield ofmastitis cows based on infrared thermography","volume":"12","author":"Khakimov","year":"2022","journal-title":"Appl. Sci.-Basel"},{"key":"10.1016\/j.compag.2026.111785_b0405","doi-asserted-by":"crossref","first-page":"31871","DOI":"10.1038\/s41598-024-83279-6","article-title":"Predictive modeling of cattle calving time emphasizing abnormal and normal cases by using posture analysis","volume":"14","author":"Khin","year":"2024","journal-title":"Sci. Rep."},{"issue":"8","key":"10.1016\/j.compag.2026.111785_b0410","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.5713\/ajas.2005.1194","article-title":"Recognition of individual Holstein cattle by imaging body patterns","volume":"18","author":"Kim","year":"2005","journal-title":"Asian-Australas. J. Anim. Sci."},{"issue":"6","key":"10.1016\/j.compag.2026.111785_b0415","doi-asserted-by":"crossref","first-page":"868","DOI":"10.5713\/ajas.2005.868","article-title":"The identification of Japanese black cattle by their faces","volume":"18","author":"Kim","year":"2005","journal-title":"Asian-Australas. J. Anim. Sci."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0420","doi-asserted-by":"crossref","first-page":"207","DOI":"10.3390\/ani11010207","article-title":"Breathing pattern analysis in cattle using infrared thermography and computer vision","volume":"11","author":"Kim","year":"2021","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.111785_b0425","doi-asserted-by":"crossref","DOI":"10.3389\/fvets.2025.1548906","article-title":"Unique temperature change patterns in calves eyes and muzzles: a non-invasive approach using infrared thermography and object detection","volume":"12","author":"Kim","year":"2025","journal-title":"Front. Vet. Sci."},{"issue":"10","key":"10.1016\/j.compag.2026.111785_b0430","doi-asserted-by":"crossref","DOI":"10.1016\/j.animal.2025.101621","article-title":"Tail tip temperature measured by thermography as an indicator of animal health in Holstein cows","volume":"19","author":"K\u00f6hler","year":"2025","journal-title":"Animal"},{"issue":"18","key":"10.1016\/j.compag.2026.111785_b0435","doi-asserted-by":"crossref","first-page":"2691","DOI":"10.3390\/ani14182691","article-title":"Infrared thermography as a diagnostic tool for the assessment of mastitis in dairy ruminants","volume":"14","author":"Korelidou","year":"2024","journal-title":"Animals"},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b0440","doi-asserted-by":"crossref","first-page":"2808","DOI":"10.3168\/jds.2024-25387","article-title":"Associations of body condition score, body condition score change, and hyperketonemia with mastitis, reproduction, and milk production","volume":"108","author":"Krogstad","year":"2025","journal-title":"J. Dairy Sci."},{"issue":"04","key":"10.1016\/j.compag.2026.111785_b0445","doi-asserted-by":"crossref","first-page":"124","DOI":"10.17221\/38\/2020-CJAS","article-title":"Evaluating the economic profit of reproductive performance through the integration of a dynamic programming model on a specific dairy farm","volume":"65","author":"Krp\u00e1lkov\u00e1","year":"2020","journal-title":"Czech J. Anim. Sci."},{"issue":"4","key":"10.1016\/j.compag.2026.111785_b0450","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1109\/TBIOM.2025.3599374","article-title":"Multi-directional shifted patch encoding with transformers for non-invasive cattle identification","volume":"7","author":"Kumar","year":"2026","journal-title":"IEEE Trans. Biom. Behav. Identity Sci."},{"issue":"5","key":"10.1016\/j.compag.2026.111785_b0455","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1007\/s10766-017-0550-x","article-title":"Group sparse representation approach for recognition of cattle on muzzle point images","volume":"46","author":"Kumar","year":"2018","journal-title":"Int. J. Parallel Prog."},{"issue":"12","key":"10.1016\/j.compag.2026.111785_b0460","doi-asserted-by":"crossref","DOI":"10.1142\/S0218001420560078","article-title":"Biometric for cattle identification using muzzle patterns","volume":"34","author":"Kusakunniran","year":"2020","journal-title":"Int. J. Pattern Recognit Artif Intell."},{"key":"10.1016\/j.compag.2026.111785_b0465","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.compag.2019.01.019","article-title":"High-precision scanning system for complete 3D cow body shape imaging and analysis of morphological traits","volume":"157","author":"Le Cozler","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0470","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compag.2019.104977","article-title":"Volume and surface area of Holstein dairy cows calculated from complete 3D shapes acquired using a high-precision scanning system: interest for body weight estimation","volume":"165","author":"Le Cozler","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0475","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.biosystemseng.2024.07.017","article-title":"IATEFF-YOLO: Focus on cow mounting detection during nighttime","volume":"246","author":"Li","year":"2024","journal-title":"Biosyst. Eng."},{"issue":"11","key":"10.1016\/j.compag.2026.111785_b0480","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.3390\/ani12111453","article-title":"Individual beef cattle identification using muzzle images and deep learning techniques","volume":"12","author":"Li","year":"2022","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.111785_b0485","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.biosystemseng.2023.04.014","article-title":"A posture-based measurement adjustment method for improving the accuracy of beef cattle body size measurement based on point cloud data","volume":"230","author":"Li","year":"2023","journal-title":"Biosyst. Eng."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0490","first-page":"350","article-title":"Automatic body condition scoring system for dairy cows in group state based on improved YOLOv5 and video analysis","volume":"15","author":"Li","year":"2025","journal-title":"Artif. Intell. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0495","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107562","article-title":"Temporal aggregation network using micromotion features for early lameness recognition in dairy cows","volume":"204","author":"Li","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0500","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.123775","article-title":"Lameness detection system for dairy cows based on instance segmentation","volume":"249","author":"Li","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b0505","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109537","article-title":"Lameness detection of dairy cows based on key frame positioning and posture analysis","volume":"227","author":"Li","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0510","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109172","article-title":"A novel lameness detection method for dairy cows based on temporal gait and spatial post features","volume":"224","author":"Li","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0515","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.123042","article-title":"Automated measurement of beef cattle body size via key point detection and monocular depth estimation","volume":"244","author":"Li","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b0520","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1016\/j.compag.2017.10.029","article-title":"Automatic individual identification of Holstein dairy cows using tailhead images","volume":"142","author":"Li","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0525","doi-asserted-by":"crossref","unstructured":"Li, X., Hu, Z., Huang, X., Feng, T., Yang, X., Li, M. (2019). Cow body condition score estimation with convolutional neural networks. 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC), Xiamen, China, IEEE.","DOI":"10.1109\/ICIVC47709.2019.8981055"},{"key":"10.1016\/j.compag.2026.111785_b0530","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106848","article-title":"A lightweight deep learning model for cattle face recognition","volume":"195","author":"Li","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"7","key":"10.1016\/j.compag.2026.111785_b0535","first-page":"1","article-title":"Researchprogressonmachinevisiontechnologyfornon-contactbody measurementoflargelivestock","volume":"41","author":"Li","year":"2025","journal-title":"Transactions of the Chinese Society of Agricultural Engineering."},{"key":"10.1016\/j.compag.2026.111785_b0540","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.biosystemseng.2022.03.006","article-title":"Fusion of RGB, optical flow and skeleton features for the detection of lameness in dairy cows","volume":"218","author":"Li","year":"2022","journal-title":"Biosyst. Eng."},{"issue":"6","key":"10.1016\/j.compag.2026.111785_b0545","doi-asserted-by":"crossref","DOI":"10.1016\/j.animal.2025.101523","article-title":"The impact of the dairy cow\u2019s position on eye and udder temperatures obtained with infra-red thermography within a walk-trough system","volume":"19","author":"Little","year":"2025","journal-title":"Animal"},{"key":"10.1016\/j.compag.2026.111785_b0550","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118550","article-title":"CowXNet: an automated cow estrus detection system","volume":"211","author":"Lodkaew","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b0555","doi-asserted-by":"crossref","unstructured":"Louca, A., J., L., 1968. Production losses in dairy cattle due to days open. J. Dairy Sci. 51(4), 537-583.","DOI":"10.3168\/jds.S0022-0302(68)87031-6"},{"key":"10.1016\/j.compag.2026.111785_b0560","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2020.121409","article-title":"A review on dairy cattle farming: is precision livestock farming the compromise for an environmental, economic and social sustainable production?","volume":"262","author":"Lovarelli","year":"2020","journal-title":"J. Clean. Prod."},{"issue":"8","key":"10.1016\/j.compag.2026.111785_b0565","doi-asserted-by":"crossref","first-page":"535","DOI":"10.3390\/ani9080535","article-title":"Infrared thermography-s non-invasive method of measuring respiration rate in calves","volume":"9","author":"Lowe","year":"2019","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.111785_b0570","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110017","article-title":"Automatic coarse-to-fine method for cattle body measurement based on improved GCN and 3D parametric model","volume":"231","author":"Lu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0575","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120365","article-title":"Algorithm for cattle identification based on locating key area","volume":"228","author":"Lu","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b0580","doi-asserted-by":"crossref","unstructured":"Luo, X., Hu, Y., Gao, Z., Damjin, B., Guo, H., Ruchay, A. (2022). Construction of statistical shape model of real cattle and its application to body measurement. 2022 IEEE Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), Perugia, Italy.","DOI":"10.1109\/MetroAgriFor55389.2022.9964568"},{"key":"10.1016\/j.compag.2026.111785_b0585","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.biosystemseng.2023.01.016","article-title":"Automated measurement of livestock body based on pose normalisation using statistical shape model","volume":"227","author":"Luo","year":"2023","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0590","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijheatmasstransfer.2024.126619","article-title":"An analytical model for the three-dimensional thermal resistance of particles considering internal heat conduction based on the generalized thermal resistance concept","volume":"240","author":"Luo","year":"2025","journal-title":"Int. J. Heat Mass Transf."},{"key":"10.1016\/j.compag.2026.111785_b0595","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.34133\/research.1047","article-title":"Orchestrating embodied systems through the embodied context protocol: motivation, progress, and directions","volume":"8","author":"Ma","year":"2025","journal-title":"Research"},{"key":"10.1016\/j.compag.2026.111785_b0600","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106772","article-title":"Basic motion behavior recognition of single dairy cow based on improved Rexnet 3D network","volume":"194","author":"Ma","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0605","first-page":"1","article-title":"Integrating artificial intelligence in dairy farm management - biometric facial recognition for cows","volume":"10","author":"Mahato","year":"2025","journal-title":"Information Processing in Agriculture."},{"key":"10.1016\/j.compag.2026.111785_b0610","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106313","article-title":"A systematic literature review on deep learning applications for precision cattle farming","volume":"187","author":"Mahmud","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0615","doi-asserted-by":"crossref","first-page":"310","DOI":"10.3168\/jdsc.2023-0442","article-title":"Predicting respiration rate in unrestrained dairy cows using image analysis and fast Fourier transform","volume":"5","author":"Mantovani","year":"2024","journal-title":"JDS Communications."},{"key":"10.1016\/j.compag.2026.111785_b0620","article-title":"Global perspectives of intensive animal farming and its applications","volume":"10","author":"Manzoor","year":"2023","journal-title":"Intech Open."},{"issue":"19","key":"10.1016\/j.compag.2026.111785_b0625","doi-asserted-by":"crossref","first-page":"6490","DOI":"10.3390\/s21196490","article-title":"An absorbing markov chain model to predict dairy cow calving time","volume":"21","author":"Maw","year":"2021","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.111785_b0630","doi-asserted-by":"crossref","unstructured":"McManus, C., Tanure, B., Peripolli, V., Seixas, L., Fischer, V., Gabbi, A., Menegassi, S., Stumpf, M., Kolling, G., DIasi, E., Costa Jr, J., 2016. Infrared thermography in animal production: An overview. Comput. Electron. Agric. 123, 10-16.","DOI":"10.1016\/j.compag.2016.01.027"},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0635","doi-asserted-by":"crossref","first-page":"9662","DOI":"10.3168\/jds.2024-26069","article-title":"Color-independent cattle identification using keypoint detection and Siamese neural networks in closed- and open-set scenarios","volume":"108","author":"Menezes","year":"2025","journal-title":"J. Dairy Sci."},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b0640","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.tvjl.2015.04.013","article-title":"Infrared thermography of the udder after experimentally induced Escherichia coli mastitis in cows","volume":"204","author":"Metzner","year":"2015","journal-title":"Vet. J."},{"key":"10.1016\/j.compag.2026.111785_b0645","article-title":"Signal-based feature analysis of behavioral trajectories for predicting calving time and classifying assistance needs","volume":"243","author":"Mg","year":"2026","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0650","doi-asserted-by":"crossref","first-page":"2378","DOI":"10.1038\/s41598-025-85932-0","article-title":"Automated system for calving time prediction and cattle classification utilizing trajectory data and movement features","volume":"15","author":"Mg","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compag.2026.111785_b0655","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.applanim.2011.03.003","article-title":"Behavioural predictors of the start of normal and dystocic calving in dairy cows and heifers","volume":"132","author":"Miedema","year":"2011","journal-title":"Appl. Anim. Behav. Sci."},{"key":"10.1016\/j.compag.2026.111785_b0660","first-page":"1","article-title":"Using 3D imaging and machine learning to predict liveweight and carcass characteristics of live finishing beef cattle","volume":"3","author":"Miller","year":"2019","journal-title":"Front. Sustainable Food Syst."},{"key":"10.1016\/j.compag.2026.111785_b0665","doi-asserted-by":"crossref","DOI":"10.1016\/j.techfore.2024.123842","article-title":"Evaluating the adoption of sensor and robotic technologies from a multi-stakeholder perspective: the case of greenhouse sector in China","volume":"210","author":"Min","year":"2025","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"10.1016\/j.compag.2026.111785_b0670","article-title":"AI-powered visual E-monitoring system for cattle health and wealth","volume":"12","author":"Moe","year":"2025","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.compag.2026.111785_b0675","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107120","article-title":"Monitoring body temperature of cattle using an innovative infrared photodiode thermometer","volume":"198","author":"Murugeswari","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"4","key":"10.1016\/j.compag.2026.111785_b0680","first-page":"724","article-title":"Multi-camera fusion and bird-eye view location mapping for deep learning-based cattle behavior monitoring","volume":"15","author":"Nasir","year":"2025","journal-title":"Artif. Intell. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0685","volume":"32","author":"Neethirajan","year":"2021","journal-title":"Digital Livestock Farming. Sens. Bio-Sens. Res."},{"key":"10.1016\/j.compag.2026.111785_b0690","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.biosystemseng.2017.11.014","article-title":"3D Computer-vision system for automatically estimating heifer height and body mass","volume":"173","author":"Nir","year":"2018","journal-title":"Biosyst. Eng."},{"issue":"12","key":"10.1016\/j.compag.2026.111785_b0695","doi-asserted-by":"crossref","first-page":"3009","DOI":"10.1017\/S175173111900199X","article-title":"Precision livestock farming: building \u2018digital representations\u2019 to bring the animals closer to the farmer","volume":"13","author":"Norton","year":"2019","journal-title":"Animal"},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0700","first-page":"618","article-title":"Reasons for culling, culling due to lameness,and economic losses in dairy cows","volume":"67","author":"Olechnowicz","year":"2011","journal-title":"Med. Weter."},{"key":"10.1016\/j.compag.2026.111785_b0705","doi-asserted-by":"crossref","DOI":"10.1109\/TIM.2025.3597695","article-title":"Interference factors and compensation methods when using infrared thermography for temperature measurement: a review","volume":"74","author":"Pan","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0710","article-title":"Enhancing digital cattle identification with fine-grained image analysis","volume":"297","author":"Pathak","year":"2026","journal-title":"Expert Syst. Appl."},{"issue":"8","key":"10.1016\/j.compag.2026.111785_b0715","doi-asserted-by":"crossref","first-page":"6178","DOI":"10.3168\/jds.2023-24065","article-title":"A dynamic individual method for yak heifer live body weight estimation using the YOLOv8 network and body parameter detection algorithm","volume":"107","author":"Peng","year":"2024","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0720","doi-asserted-by":"crossref","unstructured":"Pluk, A., Bahr, C., Leroy, T., Poursaberi, A., Song, X., Vranken, E., Maertens, W., Van Nuffel, A., D., B., 2010. Evaluation of step overlap as an automatic measure in dairy cow locomotion. Transactions of the American Society of Agricultural and Biological Engineers. 53(4), 1305-1312.","DOI":"10.13031\/2013.32580"},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0725","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.biosystemseng.2013.03.002","article-title":"A computer vision-based system for the automatic detection of lying behaviour of dairy cows in free-stall barns","volume":"115","author":"Porto","year":"2013","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0730","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.biosystemseng.2015.02.012","article-title":"The automatic detection of dairy cow feeding and standing behaviours in free-stall barns by a computer vision-based system","volume":"133","author":"Porto","year":"2015","journal-title":"Biosyst. Eng."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0735","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.compag.2010.07.004","article-title":"Real-time automatic lameness detection based on back posture extraction in dairy cattle: Shape analysis of cow with image processing techniques","volume":"74","author":"Poursaberi","year":"2010","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0740","first-page":"1","article-title":"Evaluation of sensor measurements for early identification of clinical mastitis in an automatic milking system","volume":"18","author":"Prus","year":"2025","journal-title":"J. Dairy Res."},{"key":"10.1016\/j.compag.2026.111785_b0745","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110328","article-title":"DenseDFFNet: Dense connected dual-stream feature fusion network for calf manure segmentation and diarrhea recognition","volume":"234","author":"Pu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0750","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106650","article-title":"C3D-ConvLSTM based cow behaviour classification using video data for precision livestock farming","volume":"193","author":"Qiao","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0755","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106143","article-title":"Intelligent perception for cattle monitoring: a review for cattle identification, body condition score evaluation, and weight estimation","volume":"185","author":"Qiao","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0760","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110674","article-title":"Advancing animal farming with deep learning: a systematic review","volume":"237","author":"Rahman","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"4","key":"10.1016\/j.compag.2026.111785_b0765","doi-asserted-by":"crossref","first-page":"2519","DOI":"10.3168\/jds.2022-22446","article-title":"Cost of lameness in dairy herds: an integrated bioeconomic modeling approach","volume":"106","author":"Robcis","year":"2023","journal-title":"J. Dairy Sci."},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b0770","first-page":"327","article-title":"When is a cow in estrus?","volume":"74","author":"Roelofs","year":"2010","journal-title":"Clinical and Practical Aspects. Theriogenology."},{"key":"10.1016\/j.compag.2026.111785_b0775","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105821","article-title":"Accurate body measurement of live cattle using three depth cameras and non-rigid 3-D shape recovery","volume":"179","author":"Ruchay","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0780","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106559","article-title":"T-LEAP: Occlusion-robust pose estimation of walking cows using temporal information","volume":"192","author":"Russello","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0785","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109040","article-title":"Video-based automatic lameness detection of dairy cows using pose estimation and multiple locomotion traits","volume":"223","author":"Russello","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0790","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.compag.2011.02.001","article-title":"Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis","volume":"76","author":"Sakir","year":"2011","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0795","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.biosystemseng.2017.03.001","article-title":"A multi-Kinect cow scanning system: calculating linear traits from manually marked recordings of Holstein-Friesian dairy cows","volume":"157","author":"Salau","year":"2017","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0800","first-page":"1","article-title":"Multi-modal LLMs in agriculture: a comprehensive review","volume":"23","author":"Sapkota","year":"2025","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0805","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108963","article-title":"CattNIS: Novel identification system of cattle with retinal images based on feature matching method","volume":"221","author":"Saygili","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0810","doi-asserted-by":"crossref","first-page":"2745","DOI":"10.3168\/jds.S0022-0302(94)77217-9","article-title":"The estrus detection problem: new concepts, technologies, and possibilities","volume":"77","author":"Senger","year":"1994","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0815","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109657","article-title":"Universal bovine identification via depth data and deep metric learning","volume":"229","author":"Sharma","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0820","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106495","article-title":"Automatic recognition method of cow ruminating behaviour based on edge computing","volume":"191","author":"Shen","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0825","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110206","article-title":"Redefining lameness assessment: Constructing lameness hierarchy using crowd-sourced data","volume":"234","author":"Sheng","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0830","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.107666","article-title":"Automatic estimation of dairy cow body condition score based on attention-guided 3D point cloud feature extraction","volume":"206","author":"Shi","year":"2023","journal-title":"Comput. Electron. Agric."},{"issue":"1\u20132","key":"10.1016\/j.compag.2026.111785_b0835","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/S0168-1591(99)00079-9","article-title":"A note on silent ovulation identified by using radiotelemetry for estrous detection","volume":"66","author":"Shipka","year":"2000","journal-title":"Appl. Anim. Behav. Sci."},{"issue":"11","key":"10.1016\/j.compag.2026.111785_b0840","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.3390\/agronomy11112365","article-title":"Automated muzzle detection and biometric identification via Few-Shot deep transfer learning of mixed breed cattle","volume":"11","author":"Shojaeipour","year":"2021","journal-title":"Agronomy-Basel"},{"key":"10.1016\/j.compag.2026.111785_b0845","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108678","article-title":"Non-contact respiration rate measurement of multiple cows in a free-stall barn using computer vision methods","volume":"218","author":"Shu","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0850","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.biosystemseng.2023.01.009","article-title":"Determining the onset of heat stress in a dairy herd based on automated behaviour recognition","volume":"226","author":"Shu","year":"2023","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0855","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108614","article-title":"Automated collection of facial temperatures in dairy cows via improved UNet","volume":"220","author":"Shu","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0860","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.theriogenology.2014.12.029","article-title":"Automated and visual measurements of estrous behavior and their sources of variation in Holstein heifers. I: walking activity and behavior frequency","volume":"84","author":"Silper","year":"2015","journal-title":"Theriogenology"},{"issue":"5","key":"10.1016\/j.compag.2026.111785_b0865","doi-asserted-by":"crossref","first-page":"4448","DOI":"10.3168\/jds.2017-13094","article-title":"Automated body weight prediction of dairy cows using 3-dimensional vision","volume":"101","author":"Song","year":"2018","journal-title":"J. Dairy Sci."},{"issue":"5","key":"10.1016\/j.compag.2026.111785_b0870","doi-asserted-by":"crossref","first-page":"4294","DOI":"10.3168\/jds.2018-15238","article-title":"Automated body condition scoring of dairy cows using 3-dimensional feature extraction from multiple body regions","volume":"102","author":"Song","year":"2019","journal-title":"J. Dairy Sci."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b0875","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.compag.2008.05.016","article-title":"Automatic detection of lameness in dairy cattle - Vision-based trackway analysis in cow's locomotion","volume":"64","author":"Song","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0880","doi-asserted-by":"crossref","unstructured":"Spana, Gauttam, H., Chauhan, V., Pattanaik, K., Trivedi, A., Ghosh, H., 2026. A comprehensive review of Edge computing empowered smart agriculture: Trends, opportunities and future directions. Comput. Electron. Agric. 241, 111252.","DOI":"10.1016\/j.compag.2025.111252"},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0885","doi-asserted-by":"crossref","first-page":"7714","DOI":"10.3168\/jds.2015-10607","article-title":"Development of automatic body condition scoring using a low-cost 3-dimensional Kinect camera","volume":"99","author":"Spoliansky","year":"2016","journal-title":"J. Dairy Sci."},{"issue":"6","key":"10.1016\/j.compag.2026.111785_b0890","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1016\/S0093-691X(97)00098-8","article-title":"A lameness scoring system that uses posture and gait to predict dairy cattle reproductive performance","volume":"47","author":"Sprecher","year":"1997","journal-title":"Theriogenology"},{"issue":"8","key":"10.1016\/j.compag.2026.111785_b0895","doi-asserted-by":"crossref","first-page":"1292","DOI":"10.3390\/agriculture14081292","article-title":"A review on mastitis in dairy cows research: current status and future perspectives","volume":"14","author":"Stanek","year":"2024","journal-title":"Agriculture-Basel"},{"key":"10.1016\/j.compag.2026.111785_b0900","doi-asserted-by":"crossref","first-page":"3893","DOI":"10.3168\/jds.2016-12055","article-title":"The use of infrared thermography and accelerometers for remote monitoring of dairy cow health and welfare","volume":"100","author":"Stewart","year":"2019","journal-title":"J. Dairy Sci."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0905","doi-asserted-by":"crossref","first-page":"385","DOI":"10.3390\/ani11020385","article-title":"Activity-integrated hidden markov model to predict calving time","volume":"11","author":"Sumi","year":"2021","journal-title":"Animals"},{"issue":"11","key":"10.1016\/j.compag.2026.111785_b0910","doi-asserted-by":"crossref","first-page":"10140","DOI":"10.3168\/jds.2018-16164","article-title":"Automatic monitoring system for individual dairy cows based on a deep learning framework that provides identification via body parts and estimation of body condition score","volume":"102","author":"Sun","year":"2019","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0915","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105651","article-title":"Recording the heart beat of cattle using a gradiometer system of optically pumped magnetometers","volume":"177","author":"Sutter","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0920","doi-asserted-by":"crossref","DOI":"10.1016\/j.physbeh.2024.114710","article-title":"Mounting exhibited between cows is not associated with sexual motivation","volume":"287","author":"Suzuki","year":"2024","journal-title":"Physiol. Behav."},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0925","doi-asserted-by":"crossref","first-page":"9712","DOI":"10.3168\/jds.2025-26257","article-title":"A descriptive analysis of inter- and intraobserver agreement of body condition scoring methods in dairy cattle","volume":"108","author":"Swartz","year":"2025","journal-title":"J. Dairy Sci."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0930","article-title":"Factors affecting calving to conception interval (days open) in dairy cows located at Dessie and Kombolcha towns","volume":"17","author":"Temesgen","year":"2022","journal-title":"Ethiopia. Plos ONE."},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0935","first-page":"708","article-title":"Mastitis in beef cows - Incidence, pathogens and economic significance - a literature review","volume":"87","author":"Tenhagen","year":"2006","journal-title":"Praktische Tierarzt."},{"key":"10.1016\/j.compag.2026.111785_b0940","doi-asserted-by":"crossref","DOI":"10.1016\/j.tvjl.2023.105975","article-title":"Prevalence of lameness in dairy cows: a literature review","volume":"295","author":"Thomsen","year":"2023","journal-title":"Vet. J."},{"issue":"15","key":"10.1016\/j.compag.2026.111785_b0945","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.3390\/ani13152538","article-title":"Mastitis in dairy cattle: On-farm diagnostics and future perspectives","volume":"13","author":"Tommasoni","year":"2023","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.111785_b0950","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.compag.2014.03.003","article-title":"A motion and image analysis method for automatic detection of estrus and mating behavior in cattle","volume":"104","author":"Tsai","year":"2014","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b0955","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106913","article-title":"Frequency modulated continuous wave radar-based system for monitoring dairy cow respiration rate","volume":"196","author":"Tuan","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b0960","doi-asserted-by":"crossref","first-page":"67","DOI":"10.3390\/jimaging10030067","article-title":"Revolutionizing cow welfare monitoring: a novel top-view perspective with depth camera-based lameness classification","volume":"10","author":"Tun","year":"2024","journal-title":"J. Imaging."},{"issue":"9","key":"10.1016\/j.compag.2026.111785_b0965","doi-asserted-by":"crossref","first-page":"10310","DOI":"10.3168\/jds.2020-19894","article-title":"Application of udder surface temperature by infrared thermography for diagnosis of subclinical mastitis in Holstein cows located in tropical highlands","volume":"104","author":"Velasco-Bola\u00f1os","year":"2021","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b0970","first-page":"59451","article-title":"MmCows: a multimodal dataset for dairy cattle monitoring","volume":"37","author":"Vu","year":"2024","journal-title":"Adv. Neural Inf. Proces. Syst."},{"key":"10.1016\/j.compag.2026.111785_b0975","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.112036","article-title":"Non-contact weight intelligent estimation based on yak skeleton localization","volume":"161","author":"Wang","year":"2025","journal-title":"Eng. Appl. Artif. Intel."},{"issue":"11","key":"10.1016\/j.compag.2026.111785_b0980","doi-asserted-by":"crossref","first-page":"9862","DOI":"10.3168\/jds.2023-24601","article-title":"Learning end-to-end respiratory rate prediction of dairy cows from red, green, and blue videos","volume":"107","author":"Wang","year":"2024","journal-title":"J. Dairy Sci."},{"issue":"2","key":"10.1016\/j.compag.2026.111785_b0985","doi-asserted-by":"crossref","first-page":"442","DOI":"10.3390\/ani11020442","article-title":"Contactless video-based heart rate monitoring of a resting and an anesthetized pig","volume":"11","author":"Wang","year":"2021","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.111785_b0990","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.biosystemseng.2022.08.018","article-title":"Oestrus detection in dairy cows by using atrous spatial pyramid and attention mechanism","volume":"223","author":"Wang","year":"2022","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b0995","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.123529","article-title":"An ultra-lightweight method for individual identification of cow-back pattern images in an open image set","volume":"249","author":"Wang","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b1000","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110331","article-title":"Estrus detection in dairy cows using advanced object tracking and behavioral analysis technologies","volume":"235","author":"Wang","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"40","key":"10.1016\/j.compag.2026.111785_b1005","first-page":"1","article-title":"A non-contact and fast estimating method for respiration rate of cows using machine vision","volume":"14","author":"Wang","year":"2024","journal-title":"Agriculture"},{"key":"10.1016\/j.compag.2026.111785_b1010","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108507","article-title":"A deep learning approach combining DeepLabV3+and improved YOLOv5 to detect dairy cow mastitis","volume":"216","author":"Wang","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"10","key":"10.1016\/j.compag.2026.111785_b1015","doi-asserted-by":"crossref","DOI":"10.1016\/j.animal.2022.100646","article-title":"Accurate detection of dairy cow mastitis with deep learning technology: a new and comprehensive detection method based on infrared thermal images","volume":"16","author":"Wang","year":"2022","journal-title":"Animal"},{"key":"10.1016\/j.compag.2026.111785_b1020","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107607","article-title":"E3D: an efficient 3D CNN for the recognition of dairy cow's basic motion behavior","volume":"205","author":"Wang","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1025","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110754","article-title":"Deep metric learning for individual cattle identification using coat patterns: Proposal for a best practice","volume":"238","author":"Wang","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1030","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110050","article-title":"Non-invasive monitoring for precision sheep farming: Development, challenges, and future perspectives","volume":"231","author":"Wang","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1035","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.107632","article-title":"ShuffleNet-Triplet: a lightweight re-identification network for dairy cows in natural scenes","volume":"205","author":"Wang","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1040","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112340","article-title":"Adaptive group sample with central momentum contrast loss for unsupervised individual identification of cows in changeable conditions","volume":"167","author":"Wang","year":"2024","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.compag.2026.111785_b1045","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.111230","article-title":"Performance evaluation of a state-of-the-art keypoint detection method for precision livestock farming","volume":"240","author":"Wang","year":"2026","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1050","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.biosystemseng.2025.02.005","article-title":"Detection and tracking of oestrus dairy cows based on improved YOLOv8n and TransT models","volume":"252","author":"Wang","year":"2025","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b1055","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122212","article-title":"E-YOLO: Recognition of estrus cow based on improved YOLOv8n model","volume":"238","author":"Wang","year":"2024","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b1060","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1080\/09712119.2017.1302876","article-title":"Comparison and reliability of techniques to estimate live cattle body weight","volume":"46","author":"Wangchuk","year":"2018","journal-title":"J. Appl. Anim. Res."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b1065","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.compag.2008.05.005","article-title":"Is precision livestock farming an engineer's daydream or nightmare, an animal's friend or foe, and a farmer's panacea or pitfall?","volume":"64","author":"Wathes","year":"2008","journal-title":"Comput. Electron. Agric."},{"issue":"5","key":"10.1016\/j.compag.2026.111785_b1070","doi-asserted-by":"crossref","first-page":"4541","DOI":"10.3168\/jds.2018-15761","article-title":"Technical note: Automatic evaluation of infrared thermal images by computerized active shape modeling of bovine udders challenged with Escherichia coli","volume":"102","author":"Watz","year":"2019","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b1075","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105804","article-title":"Cattle weight estimation using active contour models and regression trees Bagging","volume":"179","author":"Weber","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1080","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128019","article-title":"Cattle incremental learning identification method based on phased dynamic expansion network","volume":"285","author":"Weng","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b1085","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106871","article-title":"Cattle face recognition based on a Two-Branch convolutional neural network","volume":"196","author":"Weng","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b1090","doi-asserted-by":"crossref","first-page":"495","DOI":"10.3168\/jds.S0022-0302(82)82223-6","article-title":"A dairy cow body condition scoring system and its relationship to selected production characteristics","volume":"65","author":"Wildman","year":"1982","journal-title":"J. Dairy Sci."},{"issue":"4","key":"10.1016\/j.compag.2026.111785_b1095","doi-asserted-by":"crossref","first-page":"2963","DOI":"10.3168\/jds.2022-22501","article-title":"Monitoring the respiratory behavior of multiple cows based on computer vision and deep learning","volume":"106","author":"Wu","year":"2023","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b1100","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106016","article-title":"Using a CNN-LSTM for basic behaviors detection of a single dairy cow in a complex environment","volume":"182","author":"Wu","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1105","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.biosystemseng.2019.11.017","article-title":"Lameness detection of dairy cows based on the YOLOv3 deep learning algorithm and a relative step size characteristic vector","volume":"189","author":"Wu","year":"2020","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b1110","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.biosystemseng.2020.01.012","article-title":"Detection of the respiratory rate of standing cows by combining the Deeplab V3+semantic segmentation model with the phase-based video magnification algorithm","volume":"192","author":"Wu","year":"2020","journal-title":"Biosyst. Eng."},{"issue":"5","key":"10.1016\/j.compag.2026.111785_b1115","doi-asserted-by":"crossref","first-page":"4508","DOI":"10.3168\/jds.2021-21337","article-title":"The use of 3-dimensional imaging of Holstein cows to estimate body weight and monitor the composition of body weight change throughout lactation","volume":"105","author":"Xavier","year":"2022","journal-title":"J. Dairy Sci."},{"key":"10.1016\/j.compag.2026.111785_b1120","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106738","article-title":"Cow identification in free-stall barns based on an improved Mask R-CNN and an SVM","volume":"194","author":"Xiao","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1125","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109287","article-title":"A novel and convenient lying cow identification method based on YOLOX and CowbodyNet: a study with applications in a barn","volume":"225","author":"Xiao","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1130","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106675","article-title":"CattleFaceNet: a cattle face identification approach based on RetinaFace and ArcFace loss","volume":"193","author":"Xu","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1135","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128519","article-title":"Multi-camera multi-cow tracking under non-overhead views","volume":"291","author":"Xu","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b1140","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.111951","article-title":"Boosting cattle face recognition under uncontrolled scenes by embedding enhancement and optimization","volume":"164","author":"Xu","year":"2024","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.compag.2026.111785_b1145","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110918","article-title":"Round-the-clock accurate sheep face recognition via frequency enhancement and cross-modal embedding generation","volume":"239","author":"Xu","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2026.111785_b1150","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.inpa.2024.04.001","article-title":"Few-shot cow identification via meta-learning","volume":"12","author":"Xu","year":"2025","journal-title":"Information Processing in Agriculture."},{"key":"10.1016\/j.compag.2026.111785_b1155","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109466","article-title":"Plant leaf disease identification by parameter-efficient transformer with adapter","volume":"138","author":"Xu","year":"2024","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.compag.2026.111785_b1160","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110285","article-title":"A geodesic distance regression-based semantic keypoints detection method for pig point clouds and body size measurement","volume":"234","author":"Xu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1165","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108703","article-title":"Optimized BottleNet Transformer model with Graph Sampling and Counterfactual attention for cow individual identification","volume":"218","author":"Xu","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1170","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109668","article-title":"Entire-barn dairy cow tracking framework for multi-camera systems","volume":"229","author":"Yamamoto","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1175","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120730","article-title":"Extracting cow point clouds from multi-view RGB images with an improved YOLACT plus plus instance segmentation","volume":"230","author":"Yang","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.111785_b1180","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110333","article-title":"One-stage keypoint detection network for end-to-end cow body measurement","volume":"146","author":"Yang","year":"2025","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.compag.2026.111785_b1185","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107218","article-title":"Automated measurement of dairy cows body size via 3D point cloud data analysis","volume":"200","author":"Yang","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"4","key":"10.1016\/j.compag.2026.111785_b1190","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.inpa.2023.09.001","article-title":"Fusion of RetinaFace and improved FaceNet for individual cow identification in natural scenes","volume":"11","author":"Yang","year":"2024","journal-title":"Information Processing in Agriculture."},{"key":"10.1016\/j.compag.2026.111785_b1195","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109253","article-title":"Utilization of deep learning models to predict calving time in dairy cattle from tail acceleration data","volume":"225","author":"Yang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1200","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108171","article-title":"Non-contact sensing technology enables precision livestock farming in smart farms","volume":"212","author":"Yin","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1205","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105707","article-title":"Using an EfficientNet-LSTM for the recognition of single Cow's motion behaviours in a complicated environment","volume":"177","author":"Yin","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1210","series-title":"Detection of calf abnormal respiratory behavior based on frame difference and improved YOLOv5 method","first-page":"211","author":"Zeng","year":"2023"},{"issue":"4","key":"10.1016\/j.compag.2026.111785_b1215","first-page":"1","article-title":"Research advances and prospect of intelligent monitoring systems for the physiological indicators of beef cattle","volume":"6","author":"Zhang","year":"2024","journal-title":"Smart Agriculture."},{"key":"10.1016\/j.compag.2026.111785_b1220","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109830","article-title":"Neural network-based method for contactless estimation of carcass weight from live beef images","volume":"229","author":"Zhang","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1225","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108307","article-title":"Automatic method for quantitatively analyzing the body condition of livestock from 3D shape","volume":"214","author":"Zhang","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1230","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2021.127712","article-title":"Wearable internet of things enabled precision livestock farming in smart farms: a review of technical solutions for precise perception, biocompatibility, and sustainability monitoring","volume":"312","author":"Zhang","year":"2021","journal-title":"J. Clean. Prod."},{"key":"10.1016\/j.compag.2026.111785_b1235","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109208","article-title":"Reparation with moving least squares sampling and extraction of body sizes of beef cattle from unilateral point clouds","volume":"224","author":"Zhang","year":"2024","journal-title":"Comput. Electron. Agric."},{"issue":"13","key":"10.1016\/j.compag.2026.111785_b1240","doi-asserted-by":"crossref","first-page":"2211","DOI":"10.3390\/ani13132211","article-title":"Dairy cow mastitis detection by thermal infrared images based on CLE-UNet","volume":"13","author":"Zhang","year":"2023","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.111785_b1245","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109248","article-title":"Recent research and development of individual precision cooling systems for dairy cows - a review","volume":"225","author":"Zhang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1250","article-title":"Automatic recognition of dairy cow mastitis from thermal images by a deep learning detector","volume":"178","author":"Zhang","year":"2020","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2026.111785_b1255","first-page":"459","article-title":"Multimodal behavior recognition for dairy cow digital twin construction under incomplete modalities: a modality mapping completion network approach","volume":"15","author":"Zhang","year":"2025","journal-title":"Artif. Intell. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1260","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106784","article-title":"Compact loss for visual identification of cattle in the wild","volume":"195","author":"Zhao","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"10","key":"10.1016\/j.compag.2026.111785_b1265","doi-asserted-by":"crossref","first-page":"1939","DOI":"10.3390\/agriculture13101939","article-title":"Detection of respiratory rate of dairy cows based on infrared thermography and deep learning","volume":"13","author":"Zhao","year":"2023","journal-title":"Agriculture"},{"key":"10.1016\/j.compag.2026.111785_b1270","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.biosystemseng.2019.03.004","article-title":"Individual identification of Holstein dairy cows based on detecting and matching feature points in body images","volume":"181","author":"Zhao","year":"2019","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b1275","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.biosystemseng.2023.05.003","article-title":"Automatic lameness scoring of dairy cows based on the analysis of head- and back-hoof linkage features using machine learning methods","volume":"230","author":"Zhao","year":"2023","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.111785_b1280","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107588","article-title":"Automatic body condition scoring for dairy cows based on efficient net and convex hull features of point clouds","volume":"205","author":"Zhao","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1285","doi-asserted-by":"crossref","first-page":"0655","DOI":"10.34133\/research.0655","article-title":"Road of large language model: source, challenge, and future perspectives","volume":"8","author":"Zhao","year":"2025","journal-title":"Research"},{"key":"10.1016\/j.compag.2026.111785_b1290","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108172","article-title":"PrunedYOLO-Tracker: an efficient multi-cows basic behavior recognition and tracking technique","volume":"213","author":"Zheng","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1295","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.107618","article-title":"Cows' legs tracking and lameness detection in dairy cattle using video analysis and Siamese neural networks","volume":"205","author":"Zheng","year":"2023","journal-title":"Comput. Electron. Agric."},{"issue":"4","key":"10.1016\/j.compag.2026.111785_b1300","first-page":"783","article-title":"FGPointKAN++ point cloud segmentation and adaptive key cutting plane recognition for cow body size measurement","volume":"15","author":"Zhou","year":"2025","journal-title":"Artif. Intell. Agric."},{"key":"10.1016\/j.compag.2026.111785_b1305","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.111307","article-title":"Humanoid animal behavior labeler: an interactive annotation agent to accelerate ethological applications in precision management of animals using large vision-language models","volume":"241","author":"Zhou","year":"2026","journal-title":"Comput. Electron. Agric."}],"container-title":["Computers and Electronics in Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926003807?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926003807?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T16:48:08Z","timestamp":1779727688000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0168169926003807"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":262,"alternative-id":["S0168169926003807"],"URL":"https:\/\/doi.org\/10.1016\/j.compag.2026.111785","relation":{},"ISSN":["0168-1699"],"issn-type":[{"value":"0168-1699","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Non-contact technologies for cattle monitoring: advances and challenges towards precision livestock farming","name":"articletitle","label":"Article Title"},{"value":"Computers and Electronics in Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compag.2026.111785","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"111785"}}