{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T05:52:48Z","timestamp":1792907568013,"version":"4.5.0"},"reference-count":48,"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\/501100015335","name":"National Modern Agriculture Industry Technology System","doi-asserted-by":"publisher","award":["CARS-45-24"],"award-info":[{"award-number":["CARS-45-24"]}],"id":[{"id":"10.13039\/501100015335","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32173025"],"award-info":[{"award-number":["32173025"]}],"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":[[2026,9]]},"DOI":"10.1016\/j.compag.2026.112077","type":"journal-article","created":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T22:17:32Z","timestamp":1781907452000},"page":"112077","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":9,"special_numbering":"C","title":["A method for quantifying feeding behavior of grass carp in outdoor ponds with complex backgrounds"],"prefix":"10.1016","volume":"251","author":[{"given":"Weiqiang","family":"Ni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenqing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zequn","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9848-4549","authenticated-orcid":false,"given":"Zhangying","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compag.2026.112077_b0005","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1109\/LSP.2014.2385794","article-title":"Automatic feeding control for dense aquaculture fish tanks","volume":"22","author":"Atoum","year":"2015","journal-title":"IEEE Signal Process Lett."},{"key":"10.1016\/j.compag.2026.112077_b0010","doi-asserted-by":"crossref","unstructured":"Barraza-Guardado, R.H., Mart\u00ednez-C\u00f3rdova, L.R., Enr\u00edquez-Oca\u00f1a, F., Mart\u00ednez-Porchas, M., Porchas-Cornejo, M.A.J.C.M., 2014. Effect of shrimp farm effluent on water and sediment quality parameters off the coast of Sonora, Mexico. 40, 221-235.","DOI":"10.7773\/cm.v40i4.2424"},{"key":"10.1016\/j.compag.2026.112077_b0015","doi-asserted-by":"crossref","unstructured":"Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H., 2018. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. In \u201cEuropean Conference on Computer Vision\u201d.","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"10.1016\/j.compag.2026.112077_b0020","doi-asserted-by":"crossref","first-page":"9485","DOI":"10.1109\/TASE.2024.3507098","article-title":"Multimodal fish feeding intensity assessment in aquaculture","volume":"22","author":"Cui","year":"2024","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"issue":"1","key":"10.1016\/j.compag.2026.112077_b0025","doi-asserted-by":"crossref","DOI":"10.1111\/raq.13001","article-title":"Fish tracking, counting, and behaviour analysis in digital aquaculture: a comprehensive survey","volume":"17","author":"Cui","year":"2025","journal-title":"Rev. Aquac."},{"key":"10.1016\/j.compag.2026.112077_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2025.111132","article-title":"Enhanced audio-based fish feeding intensity recognition via decomposed visually-guided cross-modality distillation","volume":"239","author":"Cui","year":"2025","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112077_b0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.biosystemseng.2026.104468","article-title":"Dual-branch mutual learning for multi-modal to single-modal fish feeding intensity recognition in aquaculture","volume":"267","author":"Cui","year":"2026","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2026.112077_b0040","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., 2021. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. In \u201cInternational Conference on Learning Representations\u201d."},{"key":"10.1016\/j.compag.2026.112077_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.124610","article-title":"P2AT: Pyramid pooling axial transformer for real-time semantic segmentation","volume":"255","author":"Elhassan","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.112077_b0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.aquaeng.2022.102244","article-title":"Fish feeding intensity quantification using machine vision and a lightweight 3D ResNet-GloRe network","volume":"98","author":"Feng","year":"2022","journal-title":"Aquac. Eng."},{"key":"10.1016\/j.compag.2026.112077_b0055","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/0144-8609(94)00006-M","article-title":"Detection and counting of uneaten food pellets in a sea cage using image analysis","volume":"14","author":"Foster","year":"1995","journal-title":"Aquac. Eng."},{"key":"10.1016\/j.compag.2026.112077_b0060","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s13735-017-0141-z","article-title":"A review of semantic segmentation using deep neural networks","volume":"7","author":"Guo","year":"2018","journal-title":"Int. J. Multimedia Inform. Retrieval"},{"key":"10.1016\/j.compag.2026.112077_b0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106858","article-title":"Research on fish bait particles counting model based on improved MCNN","volume":"196","author":"Hou","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112077_b0070","doi-asserted-by":"crossref","first-page":"7185","DOI":"10.1109\/JSEN.2022.3151777","article-title":"A computer vision-based intelligent fish feeding system using deep learning techniques for aquaculture","volume":"22","author":"Hu","year":"2022","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.compag.2026.112077_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.aquaculture.2020.735508","article-title":"Automatic recognition methods of fish feeding behavior in aquaculture: a review","volume":"528","author":"Li","year":"2020","journal-title":"Aquaculture"},{"key":"10.1016\/j.compag.2026.112077_b0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102634","article-title":"CSWin-UNet: Transformer UNet with cross-shaped windows for medical image segmentation","volume":"113","author":"Liu","year":"2025","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.compag.2026.112077_b0090","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.aquaeng.2014.03.005","article-title":"Measuring feeding activity of fish in RAS using computer vision","volume":"60","author":"Liu","year":"2014","journal-title":"Aquac. Eng."},{"key":"10.1016\/j.compag.2026.112077_b0095","doi-asserted-by":"crossref","unstructured":"Ma, N., Zhang, X., Zheng, H.T., Sun, J., 2018. ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design. In: \u201cEuropean Conference on Computer Vision\u201d.","DOI":"10.1007\/978-3-030-01264-9_8"},{"key":"10.1016\/j.compag.2026.112077_b0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2024.108940","article-title":"An appetite assessment method for fish in outdoor ponds with anti-shadow disturbance","volume":"221","author":"Ni","year":"2024","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112077_b0105","unstructured":"Parsonage, K.D., 2001. Detection of fish-food pellets in highly-cluttered underwater images with variable illumination."},{"key":"10.1016\/j.compag.2026.112077_b0110","unstructured":"Rola, W.R., Hasan, M.R.J.F.F.T.P., 2007. Economics of aquaculture feeding practices: a synthesis of case studies undertaken in six Asian countries. 26, 1154\u20131160."},{"key":"10.1016\/j.compag.2026.112077_b0115","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., and Brox, T., 2015. U-Net: Convolutional Networks for Biomedical Image Segmentation. In: \u201cInternational Conference on Medical Image Computing and Computer-Assisted Intervention\u201d.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"10.1016\/j.compag.2026.112077_b0120","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.aquaculture.2014.04.008","article-title":"A new method for measuring group behaviours of fish shoals from recorded videos taken in near aquaculture conditions","volume":"430","author":"Sadoul","year":"2014","journal-title":"Aquaculture"},{"key":"10.1016\/j.compag.2026.112077_b0125","doi-asserted-by":"crossref","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.J.I., 2018. MobileNetV2: Inverted Residuals and Linear Bottlenecks.","DOI":"10.1109\/CVPR.2018.00474"},{"key":"10.1016\/j.compag.2026.112077_b0130","unstructured":"Simonyan, K., Zisserman, A.J.C.S., 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition."},{"key":"10.1016\/j.compag.2026.112077_b0135","doi-asserted-by":"crossref","unstructured":"Tacon, A.G.J., Forster, I.P.J.A., 2003. Aquafeeds and the environment: policy implications. 226, 181-189.","DOI":"10.1016\/S0044-8486(03)00476-9"},{"key":"10.1016\/j.compag.2026.112077_b0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.aquaeng.2021.102178","article-title":"Evaluating fish feeding intensity in aquaculture with convolutional neural networks","volume":"94","author":"Ubina","year":"2021","journal-title":"Aquac. Eng."},{"key":"10.1016\/j.compag.2026.112077_b0145","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I.J.a., 2017. Attention Is All You Need."},{"key":"10.1016\/j.compag.2026.112077_b0150","doi-asserted-by":"crossref","first-page":"3349","DOI":"10.1109\/TPAMI.2020.2983686","article-title":"Deep high-resolution representation learning for visual recognition","volume":"43","author":"Wang","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.compag.2026.112077_b0155","doi-asserted-by":"crossref","unstructured":"Wang, Q., Cheng, L., Liu, J., Li, Z., Xie, S., De Silva, S. S., Wang, Q., Cheng, L., Liu, J., Li, Z.J.R.i.A., 2016. Freshwater aquaculture in PR China: trends and prospects. 7.","DOI":"10.1111\/raq.12086"},{"key":"10.1016\/j.compag.2026.112077_b0160","doi-asserted-by":"crossref","unstructured":"Wang, Y.L., Mai, C.S., Chen, Z.L., Song, Q., Chen, Z.H., Wu, X.L. J.A.M., and Materials, 2013. Research of Intelligent Control System for Fish-Farming. 303-306, 1200-1203.","DOI":"10.4028\/www.scientific.net\/AMM.303-306.1200"},{"key":"10.1016\/j.compag.2026.112077_b0165","first-page":"545","article-title":"Behavioral spatial-temporal characteristics-based appetite assessment for fish school in recirculating aquaculture systems","author":"Wei","year":"2021","journal-title":"Aquaculture"},{"key":"10.1016\/j.compag.2026.112077_b0170","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S., 2018. CBAM: Convolutional Block Attention Module. In \u201cComputer Vision \u2013 ECCV 2018\u201d (V. Ferrari, M. Hebert, C. Sminchisescu and Y. Weiss, eds.), Vol. 11211, pp. 3-19. Springer International Publishing, Cham.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"10.1016\/j.compag.2026.112077_b0175","doi-asserted-by":"crossref","unstructured":"Wu, M., Wang, L., Huang, T., Pang, H., Liu, S., Cui, M., Xu, L., 2026. STCA-MobileViTv3: a spatiotemporal collaborative attention network for fish feeding intensity recognition in underwater videos. Aquacultural Engineering, 102695.","DOI":"10.1016\/j.aquaeng.2026.102695"},{"key":"10.1016\/j.compag.2026.112077_b0180","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.aquaeng.2015.02.001","article-title":"Development of an adaptive neural-based fuzzy inference system for feeding decision-making assessment in silver perch (Bidyanus bidyanus) culture","volume":"66","author":"Wu","year":"2015","journal-title":"Aquac. Eng."},{"key":"10.1016\/j.compag.2026.112077_b0185","unstructured":"Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J. M., Luo, P., 2021. SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers."},{"key":"10.1016\/j.compag.2026.112077_b0190","doi-asserted-by":"crossref","unstructured":"Yang, L., Yu, H., Cheng, Y., Mei, S., Duan, Y., Li, D., Chen, Y., 2021. A dual attention network based on efficientNet-B2 for short-term fish school feeding behavior analysis in aquaculture. Computers and Electronics in Agriculture 187.","DOI":"10.1016\/j.compag.2021.106316"},{"key":"10.1016\/j.compag.2026.112077_b0195","doi-asserted-by":"crossref","unstructured":"Yin, M., Yao, Z., Cao, Y., Li, X., Zhang, Z., Lin, S., Hu, H., 2020. \u201cDisentangled Non-Local Neural Networks.\u201d Cornell University Library, arXiv.org, Ithaca.","DOI":"10.1007\/978-3-030-58555-6_12"},{"key":"10.1016\/j.compag.2026.112077_b0200","doi-asserted-by":"crossref","unstructured":"Zhang, B., Wang, L., Wu, M., Che, Z., Huang, T., Liu, S., Xu, L., 2026. DF-MobileNetV4: A dual-scale adaptive attention and fused ConvBlock enhanced MobileNetV4 for underwater fish feeding behavior recognition. Information Processing in Agriculture.","DOI":"10.1016\/j.inpa.2026.04.003"},{"key":"10.1016\/j.compag.2026.112077_b0205","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.123546","article-title":"UPFormer: U-sharped perception lightweight Transformer for segmentation of field grape leaf diseases","volume":"249","author":"Zhang","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.compag.2026.112077_b0210","doi-asserted-by":"crossref","unstructured":"Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.J.I.C.S., 2016. Pyramid Scene Parsing Network.","DOI":"10.1109\/CVPR.2017.660"},{"key":"10.1016\/j.compag.2026.112077_b0215","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.aquaeng.2017.07.008","article-title":"Assessing appetite of the swimming fish based on spontaneous collective behaviors in a recirculating aquaculture system","volume":"78","author":"Zhao","year":"2017","journal-title":"Aquac. Eng."},{"key":"10.1016\/j.compag.2026.112077_b0220","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.aquaculture.2018.07.068","article-title":"Adaptive neural fuzzy inference system for feeding decision-making of grass carp (Ctenopharyngodon idellus) in outdoor intensive culturing ponds","volume":"498","author":"Zhao","year":"2019","journal-title":"Aquaculture"},{"key":"10.1016\/j.compag.2026.112077_b0225","doi-asserted-by":"crossref","DOI":"10.1016\/j.aquaculture.2020.734970","article-title":"Feed requirement determination of grass carp (Ctenopharyngodon idella) using a hybrid method of bioenergetics factorial model and fuzzy logic control technology under outdoor pond culturing systems","volume":"521","author":"Zhao","year":"2020","journal-title":"Aquaculture"},{"key":"10.1016\/j.compag.2026.112077_b0230","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.compag.2018.02.006","article-title":"Near infrared computer vision and neuro-fuzzy model-based feeding decision system for fish in aquaculture","volume":"146","author":"Zhou","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112077_b0235","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.aquaculture.2019.04.056","article-title":"Evaluation of fish feeding intensity in aquaculture using a convolutional neural network and machine vision","volume":"507","author":"Zhou","year":"2019","journal-title":"Aquaculture"},{"key":"10.1016\/j.compag.2026.112077_b0240","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.compag.2017.02.013","article-title":"Near-infrared imaging to quantify the feeding behavior of fish in aquaculture","volume":"135","author":"Zhou","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2026.112077_b0245","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Xu, M., Bai, S., Huang, T., Bai, X., 2019. Asymmetric non-local neural networks for semantic segmentation. In: \u201cProceedings of the IEEE\/CVF international conference on computer vision\u201d, pp. 593-602.","DOI":"10.1109\/ICCV.2019.00068"}],"container-title":["Computers and Electronics in Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926006721?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169926006721?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T23:22:58Z","timestamp":1785885778000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0168169926006721"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":48,"alternative-id":["S0168169926006721"],"URL":"https:\/\/doi.org\/10.1016\/j.compag.2026.112077","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":"A method for quantifying feeding behavior of grass carp in outdoor ponds with complex backgrounds","name":"articletitle","label":"Article Title"},{"value":"Computers and Electronics in Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compag.2026.112077","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":"112077"}}