{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T14:16:49Z","timestamp":1783606609423,"version":"3.55.0"},"reference-count":26,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100002365","name":"China Agricultural University","doi-asserted-by":"publisher","award":["109013"],"award-info":[{"award-number":["109013"]}],"id":[{"id":"10.13039\/501100002365","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":[[2026,9]]},"DOI":"10.1016\/j.compag.2026.112036","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T07:40:33Z","timestamp":1781682033000},"page":"112036","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["An integrated YOLO-WGAN-GP framework for cage removal and image restoration in Stacked-Cage chicken house"],"prefix":"10.1016","volume":"251","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6771-9500","authenticated-orcid":false,"given":"Yuxiao","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuetong","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianxing","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yajun","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Man","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bowen","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1289-756X","authenticated-orcid":false,"given":"Han","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compag.2026.112036_b0005","first-page":"arXiv","volume":"No. arXiv:1701.04862","author":"Arjovsky","year":"2017","journal-title":"Towards Principled Methods for Training Generative Adversarial Networks"},{"key":"10.1016\/j.compag.2026.112036_b0010","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.2026.112036_b0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.optlaseng.2024.108588","article-title":"Endoir: a GAN-based method for fiber bundle endoscope image restoration","volume":"184","author":"Chen","year":"2025","journal-title":"Opt. Lasers Eng."},{"issue":"8","key":"10.1016\/j.compag.2026.112036_b0020","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.compag.2026.112036_b0025","series-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","first-page":"5769","article-title":"Improved training of wasserstein GANs","author":"Gulrajani","year":"2017"},{"issue":"2","key":"10.1016\/j.compag.2026.112036_b0030","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s11760-020-01749-6","article-title":"A robust and efficient image de-fencing approach using conditional generative adversarial networks","volume":"15","author":"Gupta","year":"2021","journal-title":"SIViP"},{"issue":"9","key":"10.1016\/j.compag.2026.112036_b0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2025.105281","article-title":"Progress and trends of non-contact detection methods for poultry growth information: a review","volume":"104","author":"He","year":"2025","journal-title":"Poult. Sci."},{"key":"10.1016\/j.compag.2026.112036_b0040","first-page":"5967","article-title":"Image-to-image translation with Conditional Adversarial Networks","volume":"2017","author":"Isola","year":"2017","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"10.1016\/j.compag.2026.112036_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2024.105057","article-title":"ASF-YOLO: a novel YOLO model with attentional scale sequence fusion for cell instance segmentation","volume":"147","author":"Kang","year":"2024","journal-title":"Image Vis. Comput."},{"issue":"10","key":"10.1016\/j.compag.2026.112036_b0050","doi-asserted-by":"crossref","first-page":"2977","DOI":"10.3390\/s24102977","article-title":"Transforming poultry farming: a pyramid vision transformer approach for accurate chicken counting in smart farm environments","volume":"24","author":"Khanal","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2026.112036_b0055","doi-asserted-by":"crossref","first-page":"38846","DOI":"10.1109\/ACCESS.2019.2960087","article-title":"Single-image fence removal using deep convolutional neural network","volume":"8","author":"Matsui","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.compag.2026.112036_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2023.108155","article-title":"Research of soil surface image occlusion removal and inpainting based on GAN used for estimation of farmland soil moisture content","volume":"212","author":"Meng","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112036_b0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.109411","article-title":"Robotics for poultry farming: challenges and opportunities","volume":"226","author":"Ozenturk","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112036_b0070","first-page":"6047","article-title":"Dynamic snake convolution based on topological geometric constraints for tubular structure segmentation","volume":"2023","author":"Qi","year":"2023","journal-title":"IEEE\/CVF International Conference on Computer Vision (ICCV)"},{"key":"10.1016\/j.compag.2026.112036_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105216","article-title":"Agricultural robotics research applicable to poultry production: a review","volume":"169","author":"Ren","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112036_b0080","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. In N. Navab, J. Hornegger, W. M. Wells, & A. F. Frangi (Eds), Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015 (pp. 234\u2013241). Springer International Publishing. https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"10.1016\/j.compag.2026.112036_b0085","doi-asserted-by":"crossref","unstructured":"S, K., Ramalingam, K., Pazhanivelan, P., Jagadeeswaran, R., Prabu, P. C. (2024). YOLO deep learning algorithm for object detection in agriculture: A review. Journal of Agricultural Engineering, 55(4). https:\/\/doi.org\/10.4081\/jae.2024.1641.","DOI":"10.4081\/jae.2024.1641"},{"key":"10.1016\/j.compag.2026.112036_b0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.110926","article-title":"A multimodal detection method for caged diseased hens integrating behavioral and thermal features via instance segmentation","volume":"239","author":"Sun","year":"2025","journal-title":"Comput. Electron. Agric."},{"issue":"4","key":"10.1016\/j.compag.2026.112036_b0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2024.103477","article-title":"Nondestructive estimation method of live chicken leg weight based on deep learning","volume":"103","author":"Sun","year":"2024","journal-title":"Poult. Sci."},{"issue":"1","key":"10.1016\/j.compag.2026.112036_b0100","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/00439339.2024.2440102","article-title":"Leveraging the potential of convolutional neural networks in poultry farming: a 5-year overview","volume":"81","author":"Umurungi","year":"2025","journal-title":"Worlds Poultry Science Journal"},{"key":"10.1016\/j.compag.2026.112036_b0105","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.compag.2018.11.022","article-title":"Behavior-induced health condition monitoring of caged chickens using binocular vision","volume":"156","author":"Xiao","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112036_b0110","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.compag.2026.112036_b0115","first-page":"25669","article-title":"Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild","volume":"2024","author":"Yu","year":"2024","journal-title":"Ieee\/cvf Conference on Computer Vision and Pattern Recognition (cvpr)"},{"issue":"6","key":"10.1016\/j.compag.2026.112036_b0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.psj.2024.103663","article-title":"An enhancement algorithm for head characteristics of caged chickens detection based on cyclic consistent migration neural network","volume":"103","author":"Yu","year":"2024","journal-title":"Poult. Sci."},{"key":"10.1016\/j.compag.2026.112036_b0125","doi-asserted-by":"crossref","unstructured":"Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., Yang, M.-H. (2022). Restormer: Efficient transformer for high-resolution image restoration. 2022 Ieee\/Cvf Conference on Computer Vision and Pattern Recognition (Cvpr 2022), 5718\u20135729. https:\/\/doi.org\/10.1109\/CVPR52688.2022.00564.","DOI":"10.1109\/CVPR52688.2022.00564"},{"issue":"7","key":"10.1016\/j.compag.2026.112036_b0130","first-page":"2067","article-title":"Occlusion pattern discovery for object detection and occlusion reasoning","volume":"30","author":"Zhou","year":"2020","journal-title":"IEEE Trans. Circuits Syst. Video Technol."}],"container-title":["Computers and Electronics in Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926006319?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926006319?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T13:28:55Z","timestamp":1783603735000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0168169926006319"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":26,"alternative-id":["S0168169926006319"],"URL":"https:\/\/doi.org\/10.1016\/j.compag.2026.112036","relation":{},"ISSN":["0168-1699"],"issn-type":[{"value":"0168-1699","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"An integrated YOLO-WGAN-GP framework for cage removal and image restoration in Stacked-Cage chicken house","name":"articletitle","label":"Article Title"},{"value":"Computers and Electronics in Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compag.2026.112036","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":"112036"}}