{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T00:12:38Z","timestamp":1778631158897,"version":"3.51.4"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:00:00Z","timestamp":1774396800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T00:00:00Z","timestamp":1778630400000},"content-version":"vor","delay-in-days":49,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFD2000800"],"award-info":[{"award-number":["2023YFD2000800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-43523-7","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T09:40:45Z","timestamp":1774431645000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Lightweight multiscale behavior recognition for caged laying hens using an enhanced YOLOv8 framework"],"prefix":"10.1038","volume":"16","author":[{"given":"Yurong","family":"Tang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JingGe","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binbin","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Kang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhichao","family":"Mo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longshen","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingxia","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,25]]},"reference":[{"key":"43523_CR1","unstructured":"National Bureau of Statistics.Livestock product[EB\/OL]. [2024-03-20]. https:\/\/data.stats.gov.cn\/easyquery.htm?Cn=C01&zb=A060601&sj=2023 (2023)."},{"key":"43523_CR2","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.biosystemseng.2019.08.011","volume":"199","author":"V. Bloch","year":"2020","unstructured":"Bloch, V. et al. Automatic broiler temperature measuring by thermal camera. Biosystems Eng. 199, 127\u2013134 (2020).","journal-title":"Biosystems Eng."},{"issue":"1","key":"43523_CR3","doi-asserted-by":"publisher","first-page":"33","DOI":"10.3390\/ani13010033","volume":"13","author":"M. Sozzi","year":"2022","unstructured":"Sozzi, M. et al. Measuring comfort behavioursin laying hens using deep-learning tools. Anima-ls 13 (1), 33 (2022).","journal-title":"Anima-ls"},{"issue":"2","key":"43523_CR4","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1590\/1809-4430-Eng.Agric.v36n2p253-259\/2016","volume":"36","author":"FG Jacob","year":"2016","unstructured":"Jacob, F. G. et al. The use of infrared thermography in the identification of pododermatitis in broilers[J]. Engenharia Agr\u00edcola. 36 (2), 253\u2013259 (2016).","journal-title":"Engenharia Agr\u00edcola"},{"issue":"3","key":"43523_CR5","doi-asserted-by":"publisher","first-page":"859","DOI":"10.3390\/s18030859","volume":"18","author":"YR Chien","year":"2018","unstructured":"Chien, Y. R. & Chen, Y. X. An RFID-based smart nest box: an experimental study of laying performance and behavior of individual hens[J]. Sensors 18 (3), 859 (2018).","journal-title":"Sensors"},{"key":"43523_CR6","doi-asserted-by":"publisher","first-page":"107562","DOI":"10.1016\/j.compag.2022.107562","volume":"204","author":"Li","year":"2023","unstructured":"Li et al. Temporal aggregation network using micromotion features for early lameness recognition in dairy cows. Comput. Electron. Agric. 204, 107562 (2023).","journal-title":"Comput. Electron. Agric."},{"issue":"2","key":"43523_CR7","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1080\/00071668.2016.1259530","volume":"58","author":"S Amraei","year":"2017","unstructured":"Amraei, S., Abdanan, M. S. & Salari, S. Broiler weight estimation based on machine vision and artificial neural network[J]. Br. Poult. Sci. 58 (2), 200\u2013205 (2017).","journal-title":"Br. Poult. Sci."},{"issue":"7","key":"43523_CR8","doi-asserted-by":"publisher","first-page":"55","DOI":"10.3390\/ani7070055","volume":"7","author":"PS Taylor","year":"2017","unstructured":"Taylor, P. S. et al. Ranging behaviour of commercial free-range broiler chickens 2: individual variation[J]. Animals 7 (7), 55 (2017).","journal-title":"Animals"},{"key":"43523_CR9","doi-asserted-by":"publisher","first-page":"5877","DOI":"10.1007\/s13042-025-02602-3","volume":"16","author":"E Fazzari","year":"2025","unstructured":"Fazzari, E. et al. ARTEMIS: animal recognition through enhanced multimodal integration system[J]. Int. J. Mach. Learn. Cyber. 16, 5877\u20135892 (2025).","journal-title":"Int. J. Mach. Learn. Cyber"},{"key":"43523_CR10","doi-asserted-by":"publisher","unstructured":"Ng, X. L. et al. Animal Kingdom: A Large and Diverse Dataset for Animal Behavior Understanding. 2022 IEEE\/CVF Conference on Computer Vision and (CVPR), New Orleans, LA, USA, pp. 19001\u201319012, https:\/\/doi.org\/10.1109\/CVPR52688.2022.01844 (2022).","DOI":"10.1109\/CVPR52688.2022.01844"},{"key":"43523_CR11","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/j.compag.2016.03.011","volume":"123","author":"AK Mortensen","year":"2016","unstructured":"Mortensen, A. K., Lisouski, P. & Ahrendt, P. Weight prediction of broiler chickens using 3D computer vision[J]. Comput. Electron. Agric. 123, 319\u2013326 (2016).","journal-title":"Comput. Electron. Agric."},{"key":"43523_CR12","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.compag.2018.12.014","volume":"159","author":"SV Johansen","year":"2019","unstructured":"Johansen, S. V. et al. Broiler weight forecasting using dynamic neural network models with input variable selection[J]. Comput. Electron. Agric. 159, 97\u2013109 (2019).","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"43523_CR13","doi-asserted-by":"publisher","first-page":"100309","DOI":"10.1016\/j.japr.2022.100309","volume":"32","author":"JE Linhoss","year":"2023","unstructured":"Linhoss, J. E. et al. Light intensity and uniformity in commercial broiler houses using lighting programs derived from Global Animal Partnership(GAP) lighting standards[J]. J. Appl. Poult. Res. 32 (1), 100309 (2023).","journal-title":"J. Appl. Poult. Res."},{"key":"43523_CR14","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.enbuild.2018.03.056","volume":"169","author":"A Costantino","year":"2018","unstructured":"Costantino, A. et al. Climate control in broiler houses: a thermal model for the calculation of the energy use and indoor environmental conditions[J]. Energy Build. 169, 110\u2013126 (2018).","journal-title":"Energy Build."},{"key":"43523_CR15","doi-asserted-by":"publisher","first-page":"128330","DOI":"10.1016\/j.eswa.2025.128330","volume":"289","author":"D. Edoardo Fazzari","year":"2025","unstructured":"Edoardo Fazzari, D. & Romano, F. Falchi Cesare Stefanini,Animal behavior analysis methods using deep learning: A survey. Expert Syst. Appl. 289, 128330 (2025).","journal-title":"Expert Syst. Appl."},{"key":"43523_CR16","doi-asserted-by":"crossref","unstructured":"Mohialdin, A. M. & Abdullah Magdy Elbarrany and Ayman Atia. Chicken Behavior Analysis for Surveillance in Poultry Farms. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 14 (3) (2023). http:\/\/dx.doi.org\/10.14569\/IJACSA.2023.01403106.","DOI":"10.14569\/IJACSA.2023.01403106"},{"issue":"4","key":"43523_CR17","first-page":"635","volume":"46","author":"W Yao","year":"2023","unstructured":"Yao, W. et al. Poultry sub-health status monitoring and health warning prospect. J. Nanjing Agricultural Univ. 46 (4), 635\u2013644 (2023).","journal-title":"J. Nanjing Agricultural Univ."},{"key":"43523_CR18","doi-asserted-by":"publisher","first-page":"107131","DOI":"10.1016\/j.compag.2022.107131","volume":"199","author":"D. H. Wu","year":"2022","unstructured":"Wu, D. H. et al. Information perception in modern poultry farming:a review. Comput. Electron. Agric. 199, 107131 (2022).","journal-title":"Comput. Electron. Agric."},{"issue":"11","key":"43523_CR19","doi-asserted-by":"publisher","first-page":"104193","DOI":"10.1016\/j.psj.2024.104193","volume":"103","author":"X Yang","year":"2024","unstructured":"Yang, X. et al. Monitoring activity index and behaviors of cage-free hens with advanced deep learning technologies[J]. Poult. Sci. 103 (11), 104193 (2024).","journal-title":"Poult. Sci."},{"key":"43523_CR20","first-page":"45","volume":"178","author":"J Li","year":"2024","unstructured":"Li, J. et al. YOLOv8-EMA: Enhanced multi-scale feature fusion for real-time object detection. Pattern Recognit. Lett. 178, 45\u201352 (2024). (EMA integration for YOLOv8, focusing on small-object detection).","journal-title":"Pattern Recognit. Lett."},{"key":"43523_CR21","first-page":"108123","volume":"221","author":"H Zhang","year":"2025","unstructured":"Zhang, H. et al. Attention-driven YOLOv9 for fine-grained action recognition in agricultural scenes. Comput. Electron. Agric. 221, 108123 (2025). EMA-based multi-scale feature aggregation for livestock behavior analysis.","journal-title":"Comput. Electron. Agric."},{"key":"43523_CR22","first-page":"98765","volume":"11","author":"Y Wang","year":"2023","unstructured":"Wang, Y. et al. Efficient multi-scale attention for lightweight YOLO models: Application to edge-device deployment. IEEE Access. 11, 98765\u201398778 (2023). (EMA optimization for resource-constrained YOLO variants).","journal-title":"IEEE Access."},{"key":"43523_CR23","doi-asserted-by":"crossref","unstructured":"S\u00fczen, A. A., Duman, B. & \u015een, B. Benchmark analysis of jetson tx2, jetson nano and raspberry pi using deep-cnn. In: 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). 1\u20135. (IEEE, 2020).","DOI":"10.1109\/HORA49412.2020.9152915"},{"key":"43523_CR24","unstructured":"https:\/\/pypi.org\/project\/labelImg\/"},{"key":"43523_CR25","doi-asserted-by":"crossref","unstructured":"Feroz, M. A. et al. Object detection and classification from a real-time video using SSD and YOLO models. Computational Intelligence in Pattern Recognition: Proceedings of CIPR 2021. 37\u201347. (Singapore: Springer Singapore, 2021).","DOI":"10.1007\/978-981-16-2543-5_4"},{"key":"43523_CR26","unstructured":"Ilani, M. A., Banad, Y. M. & LabelImg CNN-Based Surface Defect Detection[J]. arXiv preprint arXiv:2509.05813, (2025)."},{"issue":"7","key":"43523_CR27","first-page":"4561","volume":"32","author":"J. Li","year":"2021","unstructured":"Li, J., Chen, C. & Wang, H. C2f-Net: Cross-level feature fusion for real-time object detection. IEEE Trans. Circuits Syst. Video Technol. 32 (7), 4561\u20134574 (2021).","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"43523_CR28","first-page":"12890","volume":"36","author":"A Block","year":"2023","unstructured":"Block, A., Zhang, Z., Faster, E. M. A. & Accelerated exponential moving average for efficient deep learning training. Adv. Neural Inf. Process. Syst. 36, 12890\u201312902 (2023).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"43523_CR29","doi-asserted-by":"crossref","unstructured":"Liu, G., Liu, F., Okada, T., Freeman, J. M. & Sapiro, G. Image inpainting for irregular holes using partial convolutions. In: Proc. Eur. Conf. Comput. Vis. (ECCV), Munich, Germany, pp. 85\u2013100. (2018).","DOI":"10.1007\/978-3-030-01252-6_6"},{"key":"43523_CR30","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.biosystemseng.2018.07.002","volume":"173","author":"T van Hertem","year":"2018","unstructured":"van Hertem, T. et al. Predicting broiler gait scores from activity monitoring and flock data. Biosyst. Eng. 173, 93\u2013102 (2018).","journal-title":"Biosyst. Eng."},{"key":"43523_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/rob.70123","volume":"0","author":"E Fazzari","year":"2025","unstructured":"Fazzari, E., Romano, D& F.Falchi, and C.Stefanini Real-Time Behavior Recognition Using a Legged Robot for Animal\u2013Robot Interaction. J. Field Robot. 0, 1\u201312. (2025). https:\/\/doi.org\/10.1002\/rob.70123.","journal-title":"J. Field Robot."},{"key":"43523_CR32","doi-asserted-by":"publisher","first-page":"102955","DOI":"10.1016\/j.ecoinf.2024.102955","volume":"85","author":"E Fazzari","year":"2025","unstructured":"Fazzari, E. et al. Selective state models are what you need for animal action recognition. Ecol. Inf. 85, 102955 (2025).","journal-title":"Ecol. Inf."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-43523-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-43523-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-43523-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T23:24:39Z","timestamp":1778628279000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-43523-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,25]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["43523"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-43523-7","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,25]]},"assertion":[{"value":"5 December 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"14936"}}