{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T04:15:15Z","timestamp":1793333715056,"version":"4.5.0"},"reference-count":113,"publisher":"Elsevier BV","issue":"7","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":[[2026,3,30]],"date-time":"2026-03-30T00:00:00Z","timestamp":1774828800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008065","name":"Georgia Research Alliance","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005825","name":"National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["2023-68008-39853"],"award-info":[{"award-number":["2023-68008-39853"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Poultry Science"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.psj.2026.106887","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T15:23:08Z","timestamp":1774970588000},"page":"106887","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":12,"title":["Computer vision models for precision poultry farming: A narrative review of behavioral and welfare monitoring studies"],"prefix":"10.1016","volume":"105","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2486-436X","authenticated-orcid":false,"given":"Bidur","family":"Paneru","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8959-8293","authenticated-orcid":false,"given":"Anjan","family":"Dhungana","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1004-7374","authenticated-orcid":false,"given":"Samin","family":"Dahal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Casey W.","family":"Ritz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0005-352X","authenticated-orcid":false,"given":"Woo","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8132-9048","authenticated-orcid":false,"given":"Tianming","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5378-6727","authenticated-orcid":false,"given":"Lilong","family":"Chai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.psj.2026.106887_bib0001","article-title":"Thermal imaging and advanced deep learning for automated broiler detection and counting","volume":"7","author":"Abdalshefie Abuhussein","year":"2024","journal-title":"Al-Azhar J. Agric. Eng."},{"key":"10.1016\/j.psj.2026.106887_bib0002","doi-asserted-by":"crossref","DOI":"10.1109\/TCE.2024.3409069","article-title":"Poultry health monitoring with advanced imaging: towards next-generation agricultural applications in consumer electronics","author":"Ali","year":"2024","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.psj.2026.106887_bib0003","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10888705.2023.2186788","article-title":"Impact of body-worn sensors on broiler chicken behavior and agonistic interactions","volume":"28","author":"Anderson","year":"2025","journal-title":"J. Appl. Anim. Welf. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0004","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.3390\/agriculture13061114","article-title":"Research into heat stress behavior recognition and evaluation index for yellow-feathered broilers, based on improved Cascade region-based convolutional neural network","volume":"13","author":"Bai","year":"2023","journal-title":"Agriculture"},{"key":"10.1016\/j.psj.2026.106887_bib0005","doi-asserted-by":"crossref","first-page":"6","DOI":"10.2527\/af.2017.0102","article-title":"General introduction to precision livestock farming","volume":"7","author":"Berckmans","year":"2017","journal-title":"Anim. Front."},{"key":"10.1016\/j.psj.2026.106887_bib0006","doi-asserted-by":"crossref","unstructured":"Bharti, V., and K. K. Yogi. 2024. Chicken disease detection in the poultry utilizing grey wolf optimized deep convolutional neural network. Available at https:\/\/www.researchsquare.com\/article\/rs-4635600\/v1 (verified 8 November 2024).","DOI":"10.21203\/rs.3.rs-4635600\/v1"},{"key":"10.1016\/j.psj.2026.106887_bib0007","doi-asserted-by":"crossref","first-page":"905","DOI":"10.3390\/agriengineering5020056","article-title":"A novel YOLOv6 object detector for monitoring piling behavior of cage-free laying hens","volume":"5","author":"Bist","year":"2023","journal-title":"AgriEngineering"},{"key":"10.1016\/j.psj.2026.106887_bib0008","doi-asserted-by":"crossref","first-page":"1020","DOI":"10.3390\/agriengineering5020064","article-title":"Automatic detection of cage-free dead hens with deep learning methods","volume":"5","author":"Bist","year":"2023","journal-title":"AgriEngineering"},{"key":"10.1016\/j.psj.2026.106887_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.102729","article-title":"Mislaying behavior detection in cage-free hens with deep learning technologies","volume":"102","author":"Bist","year":"2023","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.102729","article-title":"Mislaying behavior detection in cage-free hens with deep learning technologies","volume":"102","author":"Bist","year":"2023","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109481","article-title":"An automatic method for scoring poultry footpad dermatitis with deep learning and thermal imaging","volume":"226","author":"Bist","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2024.103780","article-title":"Automatic detection of bumblefoot in cage-free hens using computer vision technologies","volume":"103","author":"Bist","year":"2024","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0013","unstructured":"Bochkovskiy, A., C.-Y. Wang, and H.-Y. M. Liao. 2020. YOLOv4: optimal speed and accuracy of object detection. Available at http:\/\/arxiv.org\/abs\/2004.10934 (verified 20 March 2025)."},{"key":"10.1016\/j.psj.2026.106887_bib0014","doi-asserted-by":"crossref","first-page":"9","DOI":"10.3382\/ps\/pey319","article-title":"A review of environmental enrichment for laying hens during rearing in relation to their behavioral and physiological development","volume":"98","author":"Campbell","year":"2019","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0015","series-title":"Proceedings of the 2024 13th Iranian\/3rd International Machine Vision and Image Processing Conference (MVIP)","first-page":"1","article-title":"An end-to-end model for chicken detection in a cluttered environment","author":"Chemme","year":"2024"},{"key":"10.1016\/j.psj.2026.106887_bib0016","article-title":"Research on broiler health status recognition method based on improved YOLOv5","volume":"6","author":"Cui","year":"2023","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.psj.2026.106887_bib0017","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1071\/AN15383","article-title":"Animal welfare and efficient farming: is conflict inevitable?","volume":"57","author":"Dawkins","year":"2017","journal-title":"Anim. Prod. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0018","doi-asserted-by":"crossref","first-page":"583","DOI":"10.3382\/japr.2007-00023","article-title":"Using accelerometers to determine the cessation of activity of broilers","volume":"16","author":"Dawson","year":"2007","journal-title":"J. Appl. Poult. Res."},{"key":"10.1016\/j.psj.2026.106887_bib0019","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1017\/S1751731115001706","article-title":"Simplifying the Welfare Quality\u00ae assessment protocol for broiler chicken welfare","volume":"10","author":"De Jong","year":"2016","journal-title":"Animal"},{"key":"10.1016\/j.psj.2026.106887_bib0020","article-title":"Smartphone based detection and classification of poultry diseases from chicken fecal images using deep learning techniques","volume":"4","author":"Degu","year":"2023","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.psj.2026.106887_bib0021","series-title":"Proceedings of the 2024 5th International Conference on Innovative Trends in Information Technology (ICITIIT)","first-page":"1","article-title":"Non-intrusive detection of poultry diseases through faecal analysis using deep learning","author":"Deo","year":"2024"},{"key":"10.1016\/j.psj.2026.106887_bib0022","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s11250-024-03922-2","article-title":"Automating poultry farm management with artificial intelligence: real-time detection and tracking of broiler chickens for enhanced and efficient health monitoring","volume":"56","author":"Depuru","year":"2024","journal-title":"Trop. Anim. Health Prod."},{"key":"10.1016\/j.psj.2026.106887_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.103185","article-title":"Tracking individual broilers on video in terms of time and distance","volume":"103","author":"Doornweerd","year":"2024","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0024","unstructured":"Ehsan, T. Z., .and S. M. Mohtavipour. 2024. Broiler-Net: a deep convolutional framework for broiler behavior analysis in poultry houses. Available at https:\/\/arxiv.org\/abs\/2401.12176 (verified 6 November 2024)."},{"key":"10.1016\/j.psj.2026.106887_bib0025","series-title":"Proceedings of the 2023 5th Novel Intelligent and Leading Emerging Sciences Conference (NILES)","first-page":"33","article-title":"The use of pose estimation for abnormal behavior analysis in poultry farms","author":"Elbarrany","year":"2023"},{"key":"10.1016\/j.psj.2026.106887_bib0026","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.3390\/agriculture13081527","article-title":"YOLO-based model for automatic detection of broiler pathological phenomena through visual and thermal images in intensive poultry houses","volume":"13","author":"Elmessery","year":"2023","journal-title":"Agriculture"},{"key":"10.1016\/j.psj.2026.106887_bib0027","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.applanim.2006.05.025","article-title":"Group size, density and social dynamics in farm animals","volume":"103","author":"Estevez","year":"2007","journal-title":"Appl. Anim. Behav. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0028","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1080\/00071668.2024.2356656","article-title":"FEDM: a convolutional neural network based fertilised egg detection model","volume":"65","author":"Gong","year":"2024","journal-title":"Br. Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0029","doi-asserted-by":"crossref","first-page":"3179","DOI":"10.3390\/s20113179","article-title":"A machine vision-based method for monitoring broiler chicken floor distribution","volume":"20","author":"Guo","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.psj.2026.106887_bib0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.102784","article-title":"Automatic detection of brown hens in cage-free houses with deep learning methods","volume":"102","author":"Guo","year":"2023","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0031","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.102784","article-title":"Automatic detection of brown hens in cage-free houses with deep learning methods","volume":"102","author":"Guo","year":"2023","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0032","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.3390\/agriculture12081176","article-title":"A dead broiler inspection system for large-scale breeding farms based on deep learning","volume":"12","author":"Hao","year":"2022","journal-title":"Agriculture"},{"key":"10.1016\/j.psj.2026.106887_bib0033","doi-asserted-by":"crossref","first-page":"2141","DOI":"10.3390\/agriculture12122141","article-title":"Research on laying hens feeding behavior detection and model visualization based on convolutional neural network","volume":"12","author":"Hao","year":"2022","journal-title":"Agriculture"},{"key":"10.1016\/j.psj.2026.106887_bib0034","series-title":"Proceedings of the 2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN)","first-page":"178","article-title":"Poultry pathogen detection: using deep learning for coccidiosis identification","author":"Harshitha","year":"2024"},{"key":"10.1016\/j.psj.2026.106887_bib0035","series-title":"Proceedings of the 2023 5th International Conference on Advancements in Computing (ICAC)","first-page":"382","article-title":"Integrated AI-based system for comprehensive poultry management","author":"Hewawasam","year":"2023"},{"key":"10.1016\/j.psj.2026.106887_bib0036","series-title":"Proceedings of the 2023 5th International Conference on Advancements in Computing (ICAC)","first-page":"591","article-title":"Accurate poultry disease identification and risk assessment through object detection","author":"Hewawasam","year":"2023"},{"key":"10.1016\/j.psj.2026.106887_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2024.104314","article-title":"Behavior recognition of cage-free multi-broilers based on spatiotemporal feature learning","volume":"103","author":"Hu","year":"2024","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0038","doi-asserted-by":"crossref","first-page":"1454","DOI":"10.3382\/ps\/pev123","article-title":"Review of rearing-related factors affecting the welfare of laying hens","volume":"94","author":"Janczak","year":"2015","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0039","unstructured":"Jocher, G. 2020. Ultralytics YOLOv5. Available at https:\/\/github.com\/ultralytics\/yolov5."},{"key":"10.1016\/j.psj.2026.106887_bib114","unstructured":"Joo, K.H., Duan, S., Weimer, S.L., Teli, M.N. (2022). Birds' Eye View: Measuring Behavior and Posture of Chickens as a Metric for Their Well-Being. arXiv preprint arXiv:2205.00069."},{"key":"10.1016\/j.psj.2026.106887_bib0041","series-title":"Proceedings of the 2021 8th International Conference on Computer and Communication Engineering (ICCCE)","first-page":"265","article-title":"Detecting poultry movement for poultry behavioral analysis using the multi-object tracking (MOT) algorithm","author":"Khairunissa","year":"2021"},{"key":"10.1016\/j.psj.2026.106887_bib0042","doi-asserted-by":"crossref","first-page":"811","DOI":"10.3390\/s25030811","article-title":"Monitoring welfare of individual broiler chickens using ultra-wideband and inertial measurement unit wearables","volume":"25","author":"Khan","year":"2025","journal-title":"Sensors"},{"key":"10.1016\/j.psj.2026.106887_bib0043","doi-asserted-by":"crossref","first-page":"2426","DOI":"10.3390\/ani13152426","article-title":"Assessment of preference behavior of layer hens under different light colors and temperature environments in long-time footage using a computer vision system","volume":"13","author":"Kodaira","year":"2023","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0045","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1017\/S1751731119002155","article-title":"Review: automated techniques for monitoring the behaviour and welfare of broilers and laying hens: towards the goal of precision livestock farming","volume":"14","author":"Li","year":"2020","journal-title":"Animal."},{"key":"10.1016\/j.psj.2026.106887_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107347","article-title":"Y-BGD: broiler counting based on multi-object tracking","volume":"202","author":"Li","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0044","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.103076","article-title":"Interindividual distances and orientations of laying hens under 8 stocking densities measured by integrative deep learning techniques","volume":"102","author":"Li","year":"2023","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0046","unstructured":"Li, Y., W. Xia, and X. Yu. 2023b. Research on a deep learning-based epidemic surveillance system for live poultry transport. 60:813\u2013821."},{"key":"10.1016\/j.psj.2026.106887_bib0048","doi-asserted-by":"crossref","first-page":"3579","DOI":"10.3390\/s21113579","article-title":"Identifying images of dead chickens with a chicken removal system integrated with a deep learning algorithm","volume":"21","author":"Liu","year":"2021","journal-title":"Sensors"},{"key":"10.1016\/j.psj.2026.106887_bib0049","unstructured":"Liu, Y., H. Zhou, Z. Ni, Z. Jiang, and X. Wang. 2024. An accurate and lightweight algorithm for caged chickens detection based on deep learning. 61."},{"key":"10.1016\/j.psj.2026.106887_bib0050","doi-asserted-by":"crossref","first-page":"1861","DOI":"10.3390\/ani13111861","article-title":"Dead laying hens detection using TIR-NIR-depth images and deep learning on a commercial farm","volume":"13","author":"Luo","year":"2023","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0051","article-title":"Poultry diseases diagnostics models using deep learning","volume":"5","author":"Machuve","year":"2022","journal-title":"Front. Artif. Intell."},{"key":"10.1016\/j.psj.2026.106887_bib0052","doi-asserted-by":"crossref","first-page":"4058","DOI":"10.3390\/s25134058","article-title":"AI-powered vocalization analysis in poultry: systematic review of health, behavior, and welfare monitoring","volume":"25","author":"Manikandan","year":"2025","journal-title":"Sensors"},{"key":"10.1016\/j.psj.2026.106887_bib0053","doi-asserted-by":"crossref","first-page":"2749","DOI":"10.3390\/agriengineering6030160","article-title":"Optimizing deep learning algorithms for effective chicken tracking through image processing","volume":"6","author":"Mehdizadeh","year":"2024","journal-title":"AgriEngineering"},{"key":"10.1016\/j.psj.2026.106887_bib0054","doi-asserted-by":"crossref","first-page":"3041","DOI":"10.3390\/ani13193041","article-title":"Towards early poultry health prediction through non-invasive and computer vision-based dropping classification","volume":"13","author":"Nakrosis","year":"2023","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0055","doi-asserted-by":"crossref","first-page":"2428","DOI":"10.3390\/ani13152428","article-title":"Estimating the feeding time of individual broilers via convolutional neural network and image processing","volume":"13","author":"Nasiri","year":"2023","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0056","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108930","article-title":"Automated detection and counting of broiler behaviors using a video recognition system","volume":"221","author":"Nasiri","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0058","article-title":"Digital livestock farming","volume":"32","author":"Neethirajan","year":"2021","journal-title":"Sens. Biosens. Res."},{"key":"10.1016\/j.psj.2026.106887_bib0057","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2022.110819","article-title":"ChickTrack \u2013 A quantitative tracking tool for measuring chicken activity","volume":"191","author":"Neethirajan","year":"2022","journal-title":"Measurement"},{"key":"10.1016\/j.psj.2026.106887_bib0059","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/S0168-1591(99)00016-7","article-title":"Exploratory behaviour of young domestic fowl","volume":"63","author":"Newberry","year":"1999","journal-title":"Appl. Anim. Behav. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0060","series-title":"Proceedings of the 2023 8th International Conference on Intelligent Information Technology","first-page":"132","article-title":"Combining autoencoder and Yolov6 model for classification and disease detection in chickens","author":"Nguyen","year":"2023"},{"key":"10.1016\/j.psj.2026.106887_bib0061","article-title":"Tracking perching behavior of cage-free laying hens with deep learning technologies","author":"Paneru","year":"2024","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0062","article-title":"Tracking dustbathing behavior of cage-free laying hens with machine vision technologies","author":"Paneru","year":"2024","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0063","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.3390\/ani13091432","article-title":"Individual monitoring of activity and lameness in conventional and slower-growing breeds of broiler chickens using accelerometers","volume":"13","author":"Pearce","year":"2023","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0064","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108999","article-title":"A deep learning method based on YOLOv5 and Super Point-Super Glue for digestive disease warning and cage location backtracking in stacked cage laying hen systems","volume":"222","author":"Qin","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0066","series-title":"Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"6517","article-title":"YOLO9000: better, faster, stronger","author":"Redmon","year":"2017"},{"key":"10.1016\/j.psj.2026.106887_bib0065","series-title":"Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"779","article-title":"You only look once: unified, real-time object detection","author":"Redmon","year":"2016"},{"key":"10.1016\/j.psj.2026.106887_bib0067","doi-asserted-by":"crossref","first-page":"378","DOI":"10.3382\/ps\/pex344","article-title":"Review of environmental enrichment for broiler chickens","volume":"97","author":"Riber","year":"2018","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0068","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.applanim.2015.06.008","article-title":"Effects of variation in nest curtain design on pre-laying behaviour of domestic hens","volume":"170","author":"Ringgenberg","year":"2015","journal-title":"Appl. Anim. Behav. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0069","doi-asserted-by":"crossref","first-page":"614","DOI":"10.3390\/ani9090614","article-title":"A systematic review of precision livestock farming in the poultry sector: is technology focussed on improving bird welfare?","volume":"9","author":"Rowe","year":"2019","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109436","article-title":"Zero-shot image segmentation for monitoring thermal conditions of individual cage-free laying hens","volume":"226","author":"Saeidifar","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib113","series-title":"AIP Conference Proceedings","doi-asserted-by":"crossref","first-page":"020001","DOI":"10.1063\/5.0231888","article-title":"Automated detection of broiler chicken behaviors through the integration of 3D accelerometer sensor and machine learning techniques","volume":"3245","author":"Sakib","year":"2024"},{"key":"10.1016\/j.psj.2026.106887_bib0071","doi-asserted-by":"crossref","first-page":"2664","DOI":"10.1016\/j.procs.2023.10.258","article-title":"Lazy labels for chicken segmentation","volume":"225","author":"Schiele","year":"2023","journal-title":"Procedia Comput. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0072","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1086\/422893","article-title":"Behavioral syndromes: an integrative overview","volume":"79","author":"Sih","year":"2004","journal-title":"Q. Rev. Biol."},{"key":"10.1016\/j.psj.2026.106887_bib0073","doi-asserted-by":"crossref","first-page":"21987","DOI":"10.1007\/s00521-022-07664-w","article-title":"Detection and tracking of chickens in low-light images using YOLO network and Kalman filter","volume":"34","author":"Siriani","year":"2022","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.psj.2026.106887_bib0074","doi-asserted-by":"crossref","first-page":"33","DOI":"10.3390\/ani13010033","article-title":"Measuring comfort behaviours in laying hens using deep-learning tools","volume":"13","author":"Sozzi","year":"2022","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107545","article-title":"Tracking pecking behaviors and damages of cage-free laying hens with machine vision technologies","volume":"204","author":"Subedi","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0076","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107545","article-title":"Tracking pecking behaviors and damages of cage-free laying hens with machine vision technologies","volume":"204","author":"Subedi","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0077","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.102637","article-title":"Tracking floor eggs with machine vision in cage-free hen houses","volume":"102","author":"Subedi","year":"2023","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0078","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2023.102637","article-title":"Tracking floor eggs with machine vision in cage-free hen houses","volume":"102","author":"Subedi","year":"2023","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0079","doi-asserted-by":"crossref","first-page":"24","DOI":"10.3390\/agriengineering7020024","article-title":"Advanced deep learning methods for multiple behavior classification of cage-free laying hens","volume":"7","author":"Subedi","year":"2025","journal-title":"AgriEngineering"},{"key":"10.1016\/j.psj.2026.106887_bib0080","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.3390\/app14031005","article-title":"Tibia-YOLO: an AssistedDetection system combined with industrial CT equipment for leg diseases in broilers","volume":"14","author":"Sun","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0081","doi-asserted-by":"crossref","first-page":"1723","DOI":"10.18280\/isi.290506","article-title":"Sick and dead chicken detection system based on YOLO algorithm","volume":"29","author":"Syafaah","year":"2024","journal-title":"ISI"},{"key":"10.1016\/j.psj.2026.106887_bib0082","doi-asserted-by":"crossref","first-page":"4199","DOI":"10.1007\/s11760-023-02652-6","article-title":"A real-time detector of chicken healthy status based on modified YOLO","volume":"17","author":"Tong","year":"2023","journal-title":"SIViP"},{"key":"10.1016\/j.psj.2026.106887_bib0083","doi-asserted-by":"crossref","DOI":"10.1051\/e3sconf\/202344802064","article-title":"Detection and tracking of broiler flock movements in the chicken coop using YOLO (R Isnanto, Hadiyanto, and B Warsito, Eds.)","volume":"448","author":"Triyanto","year":"2023","journal-title":"E3S Web Conf."},{"key":"10.1016\/j.psj.2026.106887_bib0084","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.compag.2017.09.030","article-title":"Application note: labelling, a methodology to develop reliable algorithm in PLF","volume":"142","author":"Tullo","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0085","doi-asserted-by":"crossref","DOI":"10.1590\/1806-9061-2023-1891","article-title":"Comb color analysis of broilers through the video surveillance system of a poultry house","volume":"26","author":"Ty","year":"2024","journal-title":"Braz. J. Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0086","series-title":"Proceedings of the 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI)","first-page":"1","article-title":"A novel hybrid deep neural network for early detection and classification of chicken diseases","author":"Uddin","year":"2023"},{"key":"10.1016\/j.psj.2026.106887_bib0087","first-page":"104","article-title":"Automatic detection of broiler\u2019s feeding and aggressive behavior using you only look once algorithm","volume":"13","author":"Wahjuni","year":"2024","journal-title":"IJ-AI"},{"key":"10.1016\/j.psj.2026.106887_bib0090","first-page":"1","article-title":"Recognition and classification of broiler droppings based on deep convolutional neural network","volume":"2019","author":"Wang","year":"2019","journal-title":"J. Sens."},{"key":"10.1016\/j.psj.2026.106887_bib0091","doi-asserted-by":"crossref","first-page":"5471","DOI":"10.1007\/s00521-019-04645-4","article-title":"Real-time behavior detection and judgment of egg breeders based on YOLO v3","volume":"32","author":"Wang","year":"2020","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.psj.2026.106887_bib0088","unstructured":"Wang, C.-Y., A. Bochkovskiy, and H.-Y. M. Liao. 2022. YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. Available at http:\/\/arxiv.org\/abs\/2207.02696 (verified 23 January 2024)."},{"key":"10.1016\/j.psj.2026.106887_bib0089","article-title":"Application of deep learning methods in behavior recognition of laying hens","volume":"11","author":"Wang","year":"2023","journal-title":"Front. Phys."},{"key":"10.1016\/j.psj.2026.106887_bib0092","series-title":"Welfare Quality\u00ae Assessment Protocol for Poultry (Broilers, Laying Hens) Internet]","year":"2009"},{"key":"10.1016\/j.psj.2026.106887_bib0095","doi-asserted-by":"crossref","first-page":"skad249","DOI":"10.1093\/jas\/skad249","article-title":"Super-resolution fusion optimization for poultry detection: a multi-object chicken detection method","volume":"101","author":"Wu","year":"2023","journal-title":"J. Anim. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0093","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109508","article-title":"Egg production monitoring in commercial laying cages via the StrongSort-EGG tracking-by-detection model","volume":"227","author":"Wu","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0094","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.108919","article-title":"YOLO-claw: a fast and accurate method for chicken claw detection","volume":"136","author":"Wu","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.psj.2026.106887_bib0096","series-title":"Proceedings of the 2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI)","first-page":"1002","article-title":"Behavior detection algorithm of Caged White-feather broiler based on multi-scale detail feature fusion and object relation inference","author":"Xia","year":"2023"},{"key":"10.1016\/j.psj.2026.106887_bib0097","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.3390\/agriculture14091614","article-title":"Research on an identification and grasping device for dead yellow-feather broilers in flat houses based on deep learning","volume":"14","author":"Xin","year":"2024","journal-title":"Agriculture"},{"key":"10.1016\/j.psj.2026.106887_bib0107","doi-asserted-by":"crossref","DOI":"10.1016\/j.animal.2021.100269","article-title":"Classification of broiler behaviours using triaxial accelerometer and machine learning","volume":"15","author":"Yang","year":"2021","journal-title":"Animal."},{"key":"10.1016\/j.psj.2026.106887_bib0104","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.3390\/ani12151983","article-title":"A deep learning model for detecting cage-free hens on the litter floor","volume":"12","author":"Yang","year":"2022","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0100","first-page":"20","article-title":"A deep learning method for monitoring spatial distribution of cage-free hens","volume":"8","author":"Yang","year":"2023","journal-title":"Artif. Intell. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0101","first-page":"20","article-title":"A deep learning method for monitoring spatial distribution of cage-free hens","volume":"8","author":"Yang","year":"2023","journal-title":"Artif. Intell. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0102","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.106377","article-title":"An automatic classifier for monitoring applied behaviors of cage-free laying hens with deep learning","volume":"123","author":"Yang","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.psj.2026.106887_bib0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107501","article-title":"A defencing algorithm based on deep learning improves the detection accuracy of caged chickens","volume":"204","author":"Yang","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0098","doi-asserted-by":"crossref","first-page":"911","DOI":"10.3390\/ani14060911","article-title":"Deep learning methods for tracking the locomotion of individual chickens","volume":"14","author":"Yang","year":"2024","journal-title":"Animals"},{"key":"10.1016\/j.psj.2026.106887_bib0099","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2024.104193","article-title":"Monitoring activity index and behaviors of cage-free hens with advanced deep learning technologies","volume":"103","author":"Yang","year":"2024","journal-title":"Poult. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0103","doi-asserted-by":"crossref","first-page":"3704","DOI":"10.3390\/agriengineering6040211","article-title":"A machine vision system for monitoring wild birds on poultry farms to prevent avian influenza","volume":"6","author":"Yang","year":"2024","journal-title":"AgriEngineering"},{"key":"10.1016\/j.psj.2026.106887_bib0106","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109388","article-title":"A detection method for dead caged hens based on improved YOLOv7","volume":"226","author":"Yang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0108","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105284","article-title":"An experimental study of stunned state detection for broiler chickens using an improved convolution neural network algorithm","volume":"170","author":"Ye","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.psj.2026.106887_bib0109","doi-asserted-by":"crossref","DOI":"10.3389\/fvets.2022.1062559","article-title":"Leveraging SOLOv2 model to detect heat stress of poultry in complex environments","volume":"9","author":"Yu","year":"2023","journal-title":"Front. Vet. Sci."},{"key":"10.1016\/j.psj.2026.106887_bib0110","doi-asserted-by":"crossref","first-page":"47385","DOI":"10.1109\/ACCESS.2024.3382193","article-title":"Detection of leg diseases in broiler chickens based on improved YOLOv8 X-ray images","volume":"12","author":"Zhang","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.psj.2026.106887_bib0111","doi-asserted-by":"crossref","unstructured":"Zhou, Z., L. Li, H. Xue, Y. Jia, Y. Yu, Z. Xie, and Y. Gu. 2024. A method for detecting chicken open-beak behavior based on an improved Yolov8 model. Available at https:\/\/www.ssrn.com\/abstract=4860824 (verified 8 November 2024).","DOI":"10.2139\/ssrn.4860824"},{"key":"10.1016\/j.psj.2026.106887_bib0112","first-page":"44","article-title":"Novel multiple object tracking method for yellow feather broilers in a flat breeding chamber based on improved YOLOv3 and deep SORT","volume":"16","author":"Zou","year":"2023","journal-title":"Int. J. Agric. Biol. Eng."}],"container-title":["Poultry Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0032579126005158?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0032579126005158?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T15:46:53Z","timestamp":1781279213000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0032579126005158"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":113,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,7]]}},"alternative-id":["S0032579126005158"],"URL":"https:\/\/doi.org\/10.1016\/j.psj.2026.106887","relation":{},"ISSN":["0032-5791"],"issn-type":[{"value":"0032-5791","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Computer vision models for precision poultry farming: A narrative review of behavioral and welfare monitoring studies","name":"articletitle","label":"Article Title"},{"value":"Poultry Science","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.psj.2026.106887","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc. on behalf of Poultry Science Association Inc.","name":"copyright","label":"Copyright"}],"article-number":"106887"}}