{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T07:03:10Z","timestamp":1784530990835,"version":"3.55.0"},"reference-count":50,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100007934","name":"Beijing Academy of Agriculture and Forestry Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007934","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005196","name":"Chinese Academy of Agricultural Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005196","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":[[2026,10]]},"DOI":"10.1016\/j.compag.2026.112204","type":"journal-article","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T08:57:43Z","timestamp":1784278663000},"page":"112204","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["An appearance-independent multi-object tracking framework for group-housed pigs"],"prefix":"10.1016","volume":"253","author":[{"given":"Liwen","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianzhai","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangfang","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guodong","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianyu","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuqing","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compag.2026.112204_b0005","unstructured":"Aharon, N., Orfaig, R., Bobrovsky, B.-Z., 2022. BoT-SORT: Robust Associations Multi-Pedestrian Tracking. Doi: 10.48550\/ARXIV.2206.14651."},{"key":"10.1016\/j.compag.2026.112204_b0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109090","article-title":"Agricultural object detection with you only look once (YOLO) Algorithm: a bibliometric and systematic literature review","volume":"223","author":"Badgujar","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0015","doi-asserted-by":"crossref","DOI":"10.3389\/fvets.2022.1033463","article-title":"Individual behavioral correlates of tail biting in pre-finishing piglets","volume":"9","author":"Bagaria","year":"2022","journal-title":"Front. Vet. Sci."},{"key":"10.1016\/j.compag.2026.112204_b0020","doi-asserted-by":"crossref","unstructured":"Bewley, A., Ge, Z., Ott, L., Ramos, F., Upcroft, B., 2016a. Simple online and realtime tracking, in: 2016 IEEE International Conference on Image Processing (ICIP). Presented at the 2016 IEEE International Conference on Image Processing (ICIP), IEEE, Phoenix, AZ, USA, pp. 3464\u20133468. Doi: 10.1109\/ICIP.2016.7533003.","DOI":"10.1109\/ICIP.2016.7533003"},{"key":"10.1016\/j.compag.2026.112204_b0025","doi-asserted-by":"crossref","unstructured":"Bewley, A., Ge, Z., Ott, L., Ramos, F., Upcroft, B., 2016b. Simple Online and Realtime Tracking, in: 2016 IEEE International Conference on Image Processing (ICIP). pp. 3464\u20133468. Doi: 10.1109\/ICIP.2016.7533003.","DOI":"10.1109\/ICIP.2016.7533003"},{"key":"10.1016\/j.compag.2026.112204_b0030","series-title":"In: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Presented at the 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE","first-page":"9686","article-title":"Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking","author":"Cao","year":"2023"},{"key":"10.1016\/j.compag.2026.112204_b0035","doi-asserted-by":"crossref","first-page":"1988","DOI":"10.3390\/diagnostics15161988","article-title":"Enhancing YOLOv11 with Large Kernel attention and Multi-Scale Fusion for Accurate small and Multi-Lesion Bone Tumor Detection in Radiographs","volume":"15","author":"Chen","year":"2025","journal-title":"Diagnostics"},{"key":"10.1016\/j.compag.2026.112204_b0040","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0334783","article-title":"The group-housed pigs attacking and daily behaviors detection and tracking based on improved YOLOv5s and DeepSORT","volume":"20","author":"Cheng","year":"2025","journal-title":"PLoS One"},{"key":"10.1016\/j.compag.2026.112204_b0045","doi-asserted-by":"crossref","unstructured":"Dendorfer, P., Os\u0306ep, A., Milan, A., Schindler, K., Cremers, D., Reid, I., Roth, S., Leal-Taix\u00e9, L., 2021. MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking. Int. J. Comput. Vis. 129, 845\u2013881. Doi: 10.1007\/s11263-020-01393-0.","DOI":"10.1007\/s11263-020-01393-0"},{"key":"10.1016\/j.compag.2026.112204_b0050","unstructured":"Dendorfer, P., Rezatofighi, H., Milan, A., Shi, J., Cremers, D., Reid, I., Roth, S., Schindler, K., Leal-Taix\u00e9, L., 2020. MOT20: A benchmark for multi object tracking in crowded scenes. Doi: 10.48550\/ARXIV.2003.09003."},{"key":"10.1016\/j.compag.2026.112204_b0055","doi-asserted-by":"crossref","first-page":"8725","DOI":"10.1109\/TMM.2023.3240881","article-title":"StrongSORT: Make DeepSORT Great again","volume":"25","author":"Du","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.compag.2026.112204_b0060","doi-asserted-by":"crossref","first-page":"2241","DOI":"10.3390\/ani10122241","article-title":"Computer Vision Applied to Detect Lethargy through Animal Motion monitoring: a Trial on African Swine fever in Wild Boar","volume":"10","author":"Fern\u00e1ndez-Carri\u00f3n","year":"2020","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.112204_b0065","article-title":"Automated dairy cow identification and feeding behaviour analysis using a computer vision model based on YOLOv8","volume":"12","author":"Giannone","year":"2025","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.compag.2026.112204_b0070","doi-asserted-by":"crossref","DOI":"10.3389\/fvets.2021.660565","article-title":"A Systematic Review on Validated Precision Livestock Farming Technologies for Pig Production and its Potential to Assess Animal Welfare","volume":"8","author":"G\u00f3mez","year":"2021","journal-title":"Front. Vet. Sci."},{"key":"10.1016\/j.compag.2026.112204_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108009","article-title":"Enhanced camera-based individual pig detection and tracking for smart pig farms","volume":"211","author":"Guo","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0080","doi-asserted-by":"crossref","first-page":"65","DOI":"10.3390\/s25010065","article-title":"LW-YOLO11: a Lightweight Arbitrary-Oriented Ship Detection Method based on improved YOLO11","volume":"25","author":"Huang","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.112204_b0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.111070","article-title":"Behavior tracking and analysis of group-housed pigs based on deep OC-SORT","volume":"239","author":"Huang","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0090","first-page":"2275","article-title":"African Swine fever: Transmission, Spread, and Control through Biosecurity and Disinfection","volume":"15","author":"Juszkiewicz","year":"2023","journal-title":"Including Polish Trends. Viruses"},{"key":"10.1016\/j.compag.2026.112204_b0095","unstructured":"Khanam, R., Hussain, M., 2024. YOLOv11: An Overview of the Key Architectural Enhancements. Doi: 10.48550\/ARXIV.2410.17725."},{"key":"10.1016\/j.compag.2026.112204_b0100","article-title":"EOD-EMDA: a method for automatically identifying and tracking individual pigs in herds","volume":"12","author":"Li","year":"2025","journal-title":"Smart Agric. Technol."},{"key":"10.1016\/j.compag.2026.112204_b0105","doi-asserted-by":"crossref","first-page":"3182","DOI":"10.1109\/TIP.2022.3165376","article-title":"Rethinking the competition between Detection and ReID in Multiobject Tracking","volume":"31","author":"Liang","year":"2022","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.compag.2026.112204_b0110","series-title":"In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Presented at the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"936","article-title":"Feature Pyramid Networks for Object Detection","author":"Lin","year":"2017"},{"key":"10.1016\/j.compag.2026.112204_b0115","series-title":"Path Aggregation Network for Instance Segmentation","first-page":"8759","author":"Liu","year":"2018"},{"key":"10.1016\/j.compag.2026.112204_b0120","doi-asserted-by":"crossref","first-page":"1543","DOI":"10.3390\/ani15111543","article-title":"SDGTrack: a Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios","volume":"15","author":"Liu","year":"2025","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.112204_b0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108782","article-title":"ORP-Byte: a multi-object tracking method of pigs that combines Oriented RepPoints and improved Byte","volume":"219","author":"Lu","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0130","doi-asserted-by":"crossref","first-page":"17423","DOI":"10.1038\/s41598-023-44669-4","article-title":"Cow detection and tracking system utilizing multi-feature tracking algorithm","volume":"13","author":"Mar","year":"2023","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compag.2026.112204_b0135","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.tvjl.2016.09.005","article-title":"Early detection of health and welfare compromises through automated detection of behavioural changes in pigs","volume":"217","author":"Matthews","year":"2016","journal-title":"Vet. J."},{"key":"10.1016\/j.compag.2026.112204_b0140","doi-asserted-by":"crossref","DOI":"10.1093\/jas\/skae174","article-title":"Integrating computer vision algorithms and RFID system for identification and tracking of group-housed animals: an example with pigs","volume":"102","author":"Mora","year":"2024","journal-title":"J. Anim. Sci."},{"key":"10.1016\/j.compag.2026.112204_b0145","article-title":"Accelerometer-based detection of african swine fever infection in wild boar","volume":"290","author":"Morelle","year":"2023","journal-title":"Proc. R. Soc. B Biol. Sci."},{"key":"10.1016\/j.compag.2026.112204_b0150","article-title":"A comprehensive review on YOLO versions for object detection","volume":"70","author":"Murat","year":"2025","journal-title":"Eng. Sci. Technol. Int. J."},{"key":"10.1016\/j.compag.2026.112204_b0155","doi-asserted-by":"crossref","first-page":"532","DOI":"10.3390\/s23010532","article-title":"Comparing State-of-the-Art Deep Learning Algorithms for the Automated Detection and Tracking of Black cattle","volume":"23","author":"Myat Noe","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.112204_b0160","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.biosystemseng.2025.02.001","article-title":"Re-identification for long-term tracking and management of health and welfare challenges in pigs","volume":"251","author":"Odo","year":"2025","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.112204_b0165","volume":"animal 19","author":"Orsini","year":"2025","journal-title":"Activity and Synchrony Patterns Obtained by a Tracking-by-Detection Algorithm as Potential Predictors of Tail Biting at Pen and Individual Level in Pigs."},{"key":"10.1016\/j.compag.2026.112204_b0170","author":"Shirke","year":"2021","journal-title":"Tracking Grow-Finish Pigs across Large Pens Using Multiple Cameras."},{"key":"10.1016\/j.compag.2026.112204_b0175","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.applanim.2009.09.011","article-title":"Predicting tail-biting from behaviour of pigs prior to outbreaks","volume":"121","author":"Statham","year":"2009","journal-title":"Appl. Anim. Behav. Sci."},{"key":"10.1016\/j.compag.2026.112204_b0180","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2025.1707501","article-title":"YOLO-PLNet: a lightweight real-time detection model for peanut leaf diseases based on edge deployment","volume":"16","author":"Sun","year":"2025","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.compag.2026.112204_b0185","doi-asserted-by":"crossref","unstructured":"T. Psota, E., Schmidt, T., Mote, B., C. P\u00e9rez, L., 2020. Long-Term Tracking of Group-Housed Livestock Using Keypoint Detection and MAP Estimation for Individual Animal Identification. Sensors 20, 3670. Doi: 10.3390\/s20133670.","DOI":"10.3390\/s20133670"},{"key":"10.1016\/j.compag.2026.112204_b0190","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108997","article-title":"Tracking and monitoring of individual pig behavior based on YOLOv5-Byte","volume":"221","author":"Tu","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110935","article-title":"The OKByte-AR: a multi-stage MOT framework for identifying aggressive interactions in pigs","volume":"239","author":"Tu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0200","doi-asserted-by":"crossref","first-page":"2828","DOI":"10.3390\/ani14192828","article-title":"Tracking and Behavior Analysis of Group-Housed Pigs based on a Multi-Object Tracking Approach","volume":"14","author":"Tu","year":"2024","journal-title":"Animals"},{"key":"10.1016\/j.compag.2026.112204_b0205","doi-asserted-by":"crossref","first-page":"1158","DOI":"10.3390\/agriculture14071158","article-title":"RpTrack: Robust Pig Tracking with Irregular Movement Processing and Behavioral Statistics","volume":"14","author":"Tu","year":"2024","journal-title":"Agriculture"},{"key":"10.1016\/j.compag.2026.112204_b0210","article-title":"Individual Detection and Tracking of Group Housed Pigs in their Home Pen using Computer Vision","volume":"2","author":"Der Zande","year":"2021","journal-title":"Front. Anim. Sci."},{"key":"10.1016\/j.compag.2026.112204_b0215","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.3390\/agriculture15131353","article-title":"Tomato Yield Estimation using an improved Lightweight YOLO11n Network and an Optimized Region Tracking-counting Method","volume":"15","author":"Wang","year":"2025","journal-title":"Agriculture"},{"key":"10.1016\/j.compag.2026.112204_b0220","author":"Wang","year":"2021","journal-title":"Track without Appearance: Learn Box and Tracklet Embedding with Local and Global Motion Patterns for Vehicle Tracking."},{"key":"10.1016\/j.compag.2026.112204_b0225","series-title":"Simple Online and Realtime Tracking with a Deep Association Metric","first-page":"3645","author":"Wojke","year":"2017"},{"key":"10.1016\/j.compag.2026.112204_b0230","author":"Wojke","year":"2017","journal-title":"Simple Online and Realtime Tracking with a Deep Association Metric."},{"key":"10.1016\/j.compag.2026.112204_b0235","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109205","article-title":"Long-term video activity monitoring and anomaly alerting of group-housed pigs","volume":"224","author":"Yang","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0240","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110540","article-title":"FTO-SORT: a fast track-id optimizer for enhanced multi-object tracking with SORT in unseen pig farm environments","volume":"237","author":"Yu","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112204_b0245","doi-asserted-by":"crossref","first-page":"3069","DOI":"10.1007\/s11263-021-01513-4","article-title":"FairMOT: on the Fairness of Detection and Re-identification in Multiple Object Tracking","volume":"129","author":"Zhang","year":"2021","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.compag.2026.112204_b0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110369","article-title":"Motion-guided and occlusion-aware multi-object tracking with hierarchical matching","volume":"151","author":"Zheng","year":"2024","journal-title":"Pattern Recogn."}],"container-title":["Computers and Electronics in Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926008008?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926008008?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T06:20:42Z","timestamp":1784528442000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0168169926008008"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":50,"alternative-id":["S0168169926008008"],"URL":"https:\/\/doi.org\/10.1016\/j.compag.2026.112204","relation":{},"ISSN":["0168-1699"],"issn-type":[{"value":"0168-1699","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"An appearance-independent multi-object tracking framework for group-housed pigs","name":"articletitle","label":"Article Title"},{"value":"Computers and Electronics in Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compag.2026.112204","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":"112204"}}