{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T09:42:18Z","timestamp":1772530938310,"version":"3.50.1"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T00:00:00Z","timestamp":1664323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T00:00:00Z","timestamp":1664323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s11042-022-13771-6","type":"journal-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T10:04:07Z","timestamp":1664359447000},"page":"13649-13665","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A light-weight and accurate pig detection method based on complex scenes"],"prefix":"10.1007","volume":"82","author":[{"given":"Jing","family":"Sha","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gong-Li","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi-Feng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,28]]},"reference":[{"key":"13771_CR1","doi-asserted-by":"crossref","unstructured":"Andrew W, Greatwood C, Burghardt T (2017) Visual localisation and individual identification of holstein friesian cattle via deep learning. In: Proceedings of the IEEE international conference on computer vision workshops, pp 2850\u20132859","DOI":"10.1109\/ICCVW.2017.336"},{"key":"13771_CR2","doi-asserted-by":"crossref","unstructured":"Bodla N, Singh B, Chellappa R, et al. (2017) \u201cSoft-NMS-improving object detection with one line of code.\u201d Proceedings of the IEEE International Conference on Computer Vision. Los Alamitos: IEEE Computer Society Press, pp. 5561\u20135569","DOI":"10.1109\/ICCV.2017.593"},{"key":"13771_CR3","doi-asserted-by":"crossref","unstructured":"Chen X, Xu Y, Wong DW, Wong TY, Liu J (2015) \u201cGlaucoma detection based on deep convolutional neural network.\u201d 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) pp.715\u2013718","DOI":"10.1109\/EMBC.2015.7318462"},{"key":"13771_CR4","doi-asserted-by":"crossref","unstructured":"Girshick R (2015) \u201cFast R-CNN.\u201d Proceedings IEEE Int Conf Comput Vis, 1440-1448","DOI":"10.1109\/ICCV.2015.169"},{"key":"13771_CR5","doi-asserted-by":"crossref","unstructured":"Han S, Zhang J, Zhu M, Wu J, Kong F (2017) Review of automatic detection of pig behaviours by using image analysis.\u00a0IOP Conf Ser Earth Environ Sci 69(1):012096","DOI":"10.1088\/1755-1315\/69\/1\/012096"},{"key":"13771_CR6","doi-asserted-by":"crossref","unstructured":"He K, Gkioxari G, Doll\u00e1r P\u00a0Girshick R (2017) Mask r-cnn. In: Proceedings of the IEEE international conference on computer vision, pp 2961\u20132969","DOI":"10.1109\/ICCV.2017.322"},{"key":"13771_CR7","doi-asserted-by":"crossref","unstructured":"Lin TY, Doll\u00e1r P, Girshick R, He K, Hariharan B, Belongie S (2017) Feature pyramid networks for object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2117\u20132125","DOI":"10.1109\/CVPR.2017.106"},{"key":"13771_CR8","doi-asserted-by":"crossref","unstructured":"Lin TY, Goyal P, Girshick R, He K, Doll\u00e1r P (2017) Focal loss for dense object detection. In: Proceedings of the IEEE international conference on computer vision, pp 2980\u20132988","DOI":"10.1109\/ICCV.2017.324"},{"key":"13771_CR9","doi-asserted-by":"crossref","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu CY, Berg AC (2016) Ssd: Single shot multibox detector. In: European conference on computer vision, pp 21\u201337","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"13771_CR10","doi-asserted-by":"crossref","unstructured":"Long J, Shelhamer E, Darrell T (2015) Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3431\u20133440","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"13771_CR11","doi-asserted-by":"crossref","unstructured":"Ma C, Li Y, Yin G, Ji J (2012) The monitoring and information management system of pig breeding process based on internet of things. In:\u00a02012 Fifth International Conference on Information and Computing Science, pp 103\u2013106","DOI":"10.1109\/ICIC.2012.61"},{"key":"13771_CR12","doi-asserted-by":"crossref","unstructured":"Neubeck A, Gool L J V (2006) \u201cEfficient non-maximum suppression.\u201d International Conference on Pattern Recognition. IEEE Computer Society","DOI":"10.1109\/ICPR.2006.479"},{"issue":"3","key":"13771_CR13","doi-asserted-by":"publisher","first-page":"570","DOI":"10.1109\/TIM.2015.2507378","volume":"65","author":"M Omidyeganeh","year":"2016","unstructured":"Omidyeganeh M, Shirmohammadi S, Abtahi S, Khurshid A, Farhan M, Scharcanski J, Hariri B, Laroche D, Martel L (2016) Yawning detection using embedded smart cameras. IEEE Trans Instrum Meas 65(3):570\u2013582","journal-title":"IEEE Trans Instrum Meas"},{"issue":"4","key":"13771_CR14","doi-asserted-by":"publisher","first-page":"852","DOI":"10.3390\/s19040852","volume":"19","author":"ET Psota","year":"2019","unstructured":"Psota ET, Mittek M, P\u00e9rez LC, Schmidt T, Mote B (2019) Multi-pig part detection and association with a fully-convolutional network. Sensors 19(4):852","journal-title":"Sensors"},{"key":"13771_CR15","doi-asserted-by":"crossref","unstructured":"Redmon J, Farhadi A (2017) YOLO9000: better, faster, stronger. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7263\u20137271","DOI":"10.1109\/CVPR.2017.690"},{"key":"13771_CR16","unstructured":"Redmon J, Farhadi A (2018) \u201cYOLOv3: An incremental improvement.\u201d [2022-03-03]. USA: https:\/\/arxiv.org\/abs\/1804.02767"},{"key":"13771_CR17","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala S, Girshick R, et al. (2016) \u201cYou only look once: unified, real-time object detection.\u201d Proceedings of the IEEE conference on computer vision and pattern recognition pp 779-788","DOI":"10.1109\/CVPR.2016.91"},{"key":"13771_CR18","unstructured":"Ren S, He K, Girshick R, et al. (2015) \u201cFaster R-CNN: towards real-time object detection with region proposal networks.\u201d Adv Neural Inf Process Syst91-99"},{"issue":"8","key":"13771_CR19","doi-asserted-by":"publisher","first-page":"1222","DOI":"10.3390\/s16081222","volume":"16","author":"I Sa","year":"2016","unstructured":"Sa I, Ge Z, Dayoub F et al (2016) DeepFruits: A fruit detection system using deep neural networks. Sensors 16(8):1222","journal-title":"Sensors"},{"key":"13771_CR20","doi-asserted-by":"publisher","first-page":"266","DOI":"10.3390\/sym11020266","volume":"11","author":"J Sa","year":"2019","unstructured":"Sa J, Choi Y, Lee H, Chung Y, Park D, Cho J (2019) Fast pig detection with a top-view camera under various illumination conditions. Symmetry. 11:266 (2019)","journal-title":"Symmetry."},{"key":"13771_CR21","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","volume":"61","author":"J Schmidhuber","year":"2015","unstructured":"Schmidhuber J (2015) Deep learning in neural networks: An overview. Neural Netwo Off J Int Neural Netw Soc 61:85\u2013117","journal-title":"Neural Netwo Off J Int Neural Netw Soc"},{"issue":"10","key":"13771_CR22","doi-asserted-by":"publisher","first-page":"2878","DOI":"10.3390\/app10082878","volume":"2020","author":"J Seo","year":"2020","unstructured":"Seo J, Ahn H, Kim D, Lee S, Chung Y, Park D (2020) EmbeddedPigDet\u2014fast and accurate pig detection for embedded board implementations. Appl Sci 2020(10):2878","journal-title":"Appl Sci"},{"key":"13771_CR23","doi-asserted-by":"crossref","unstructured":"Shafiee MJ, Chywl B, Li F, Wong A (2017) Fast YOLO: A fast you only look once system for real-time embedded object detection in video, pp 1709\u20131712","DOI":"10.15353\/vsnl.v3i1.171"},{"key":"13771_CR24","doi-asserted-by":"publisher","first-page":"105214","DOI":"10.1016\/j.compag.2020.105214","volume":"169","author":"R Shi","year":"2020","unstructured":"Shi R, Li T, Yamaguchi Y (2020) An attribution-based pruning method for real-time mango detection with YOLO network. Comput Electron Agric 169:105214","journal-title":"Comput Electron Agric"},{"key":"13771_CR25","doi-asserted-by":"crossref","unstructured":"Sun S, Qin J, Xue H (2019) Sheep delivery scene detection based on faster-RCNN. In:\u00a02019 International Conference on Image and Video Processing, and Artificial Intelligence, pp 297\u2013303","DOI":"10.1117\/12.2538904"},{"key":"13771_CR26","doi-asserted-by":"crossref","unstructured":"Wang J, Aozhi L, Jing X (2018) \u201cVideo-based pigs recognition with feature-integrated transfer learning.\u201d Biom Recognition, pp.620\u2013631","DOI":"10.1007\/978-3-319-97909-0_66"},{"key":"13771_CR27","doi-asserted-by":"publisher","first-page":"123757","DOI":"10.1109\/ACCESS.2019.2928603","volume":"7","author":"D Xiao","year":"2019","unstructured":"Xiao D, Shan F, Li Z, Le BT, Liu X, Li X (2019) A target detection model based on improved tiny-Yolov3 under the environment of mining truck. IEEE Access 7:123757\u2013123764","journal-title":"IEEE Access"},{"key":"13771_CR28","doi-asserted-by":"crossref","unstructured":"Yang Z, Xu W, Wang Z, He X, Yang F, Yin Z (2019) Combining YOLOV3-tiny model with dropblock for tiny-face detection. In:\u00a02019 IEEE 19th International Conference on Communication Technology (ICCT), pp 1673\u20131677","DOI":"10.1109\/ICCT46805.2019.8947158"},{"key":"13771_CR29","doi-asserted-by":"crossref","unstructured":"Zhang L, Gray H, Ye X, Collins L, Allinson N (2019) Automatic individual pig detection and tracking in pig farms. Sensors 19(5):1188","DOI":"10.3390\/s19051188"},{"key":"13771_CR30","doi-asserted-by":"crossref","unstructured":"Zhiqiang W, Jun L (2017) A review of object detection based on convolutional neural network. In:\u00a02017 36th Chinese control conference (CCC), pp 11104\u201311109","DOI":"10.23919\/ChiCC.2017.8029130"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13771-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-13771-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13771-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T10:39:59Z","timestamp":1679395199000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-13771-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,28]]},"references-count":30,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["13771"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-13771-6","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,28]]},"assertion":[{"value":"6 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 March 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 September 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 September 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"There are no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interests\/competing interests"}}]}}