{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:37:12Z","timestamp":1775839032539,"version":"3.50.1"},"reference-count":14,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T00:00:00Z","timestamp":1624233600000},"content-version":"vor","delay-in-days":171,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"crossref","award":["2019YFD0901801"],"award-info":[{"award-number":["2019YFD0901801"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Fish killing machines can effectively relieve the workers from the backbreaking labour. Generally, it is necessary to ensure the fish to be in unified posture before being input into the automatic fish killing machine. As such, how to detect the actual posture of fish in real time is a new and meaningful issue. Considering that in the actual situation, we only need to determine the four postures which are related to the head, tail, back, and belly of the fish, and we transfer this task into a four\u2010kind classification problem. As such, the convolutional neural network (CNN) is introduced here to do classification and then to detect the fish\u2019s posture. Before training the network, all sample images are preprocessed to make the fish be horizontal on the image according to the principal component analysis. Meanwhile, the histogram equalization is used to make the grey distribution of different images be close. After that, two kinds of strategies are taken to do classification. The first is a paired binary classification CNN and the second is a four\u2010category CNN. In addition, three kinds of CNN are adopted. By comparison, the four\u2010kind classification can obtain better results with error less than 1\/1000.<\/jats:p>","DOI":"10.1155\/2021\/9939688","type":"journal-article","created":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T22:20:22Z","timestamp":1624314022000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Convolutional Neural Network\u2010Based Fish Posture Classification"],"prefix":"10.1155","volume":"2021","author":[{"given":"Xin","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anzi","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaojie","family":"Mei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7604-0098","authenticated-orcid":false,"given":"Wenjin","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0986-6906","authenticated-orcid":false,"given":"Wenguang","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,6,21]]},"reference":[{"key":"e_1_2_9_1_2","first-page":"33","article-title":"Control system design of auto fish processing equipment based on plc","volume":"9","author":"Feng L.","year":"2015","journal-title":"Mechanical Engineer"},{"key":"e_1_2_9_2_2","first-page":"168","article-title":"Design of a small automatic fish killing machine","volume":"2","author":"Zhao L.","year":"2018","journal-title":"Modern Manufacturing Technology and Equipment"},{"key":"e_1_2_9_3_2","first-page":"9","article-title":"Design of small integrated scale machine","volume":"2","author":"He Q.","year":"2021","journal-title":"Technology Wind"},{"key":"e_1_2_9_4_2","first-page":"226","article-title":"Fish eye recognition based on weighted constraint adaboost and pupil diameter automatic measurement with improved hough circle transform","volume":"3323","author":"Hu Z.","year":"2017","journal-title":"Nongye Gongcheng Xuebao\/Transactions of the Chinese Society of Agricultural Engineering"},{"key":"e_1_2_9_5_2","first-page":"27","article-title":"A preliminary study on automatic shape evaluation of blood parakeet fish based on image processing","volume":"9","author":"Ma G.","year":"2019","journal-title":"Information Technology and Informatization"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1117\/1.1329338"},{"key":"e_1_2_9_7_2","first-page":"1842","article-title":"A simple and fast algorithm for l1-norm kernel pca","volume":"428","author":"Cheolmin K.","year":"2020","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_2_9_8_2","first-page":"91","article-title":"Harris corner detection algorithm optimization based on otsu","volume":"112","author":"Wang L.","year":"2018","journal-title":"Recent Advances in Electrical and Electronic Engineering"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcsi.2020.3010634"},{"key":"e_1_2_9_10_2","unstructured":"SimonyanK.andZissermanA. Very deep convolutional networks for large-scale image recognition 2015 arXiv:1409.1556."},{"key":"e_1_2_9_11_2","first-page":"940","article-title":"Detection of pulmonary nodules based on improved vgg-16 convolution neural network","volume":"374","author":"Cao Y.","year":"2020","journal-title":"Chinese Journal of Medical Physics"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09914-2"},{"key":"e_1_2_9_13_2","doi-asserted-by":"crossref","unstructured":"HeK. ZhangX. andRenS. Deep residual learning for image recognition Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition June 2016 Las Vegas NV USA IEEE 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2020.112178"}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/9939688.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2021\/9939688.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/9939688","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T22:22:09Z","timestamp":1723242129000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/9939688"}},"subtitle":[],"editor":[{"given":"Danilo","family":"Comminiello","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":14,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/9939688"],"URL":"https:\/\/doi.org\/10.1155\/2021\/9939688","archive":["Portico"],"relation":{},"ISSN":["1076-2787","1099-0526"],"issn-type":[{"value":"1076-2787","type":"print"},{"value":"1099-0526","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-03-22","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-06-11","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-06-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"9939688"}}