{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T14:48:27Z","timestamp":1777042107703,"version":"3.51.4"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T00:00:00Z","timestamp":1687219200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T00:00:00Z","timestamp":1687219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["B220202020"],"award-info":[{"award-number":["B220202020"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s11042-023-15837-5","type":"journal-article","created":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T13:02:23Z","timestamp":1687266143000},"page":"10233-10246","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["An effective automatic object detection algorithm for continuous sonar image sequences"],"prefix":"10.1007","volume":"83","author":[{"given":"Pengfei","family":"Shi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huanru","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinnan","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuan","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,20]]},"reference":[{"key":"15837_CR1","unstructured":"Bochkovskiy A, Wang C-Y, Mark Liao H-Y (2020) Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934"},{"key":"15837_CR2","doi-asserted-by":"crossref","unstructured":"Chollet F (2017) Xception: Deep learning with depthwise separable convolutions. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1251\u20131258","DOI":"10.1109\/CVPR.2017.195"},{"issue":"2","key":"15837_CR3","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1109\/JOE.2005.850931","volume":"30","author":"E Dura","year":"2005","unstructured":"Dura E, Zhang Y, Liao X, Dobeck GJ, Carin L (2005) Active learning for detection of mine-like objects in side-scan sonar imagery. IEEE J Ocean Eng 30(2):360\u2013371","journal-title":"IEEE J Ocean Eng"},{"key":"15837_CR4","first-page":"1","volume-title":"Detection and segmentation of underwater objects from forward-looking sonar based on a modified mask rcnn","author":"Z Fan","year":"2021","unstructured":"Fan Z, Xia W, Liu X, Li H (2021) Detection and segmentation of underwater objects from forward-looking sonar based on a modified mask rcnn. Signal, Image and Video Processing, pp 1\u20139"},{"key":"15837_CR5","doi-asserted-by":"crossref","unstructured":"Feichtenhofer C, Pinz A, Zisserman A (2017) Detect to track and track to detect. In Proceedings of the IEEE International Conference on Computer Vision, pp 3038\u20133046","DOI":"10.1109\/ICCV.2017.330"},{"key":"15837_CR6","unstructured":"Guo J, Li Y, Lin W, Chen Y, Li J (2018) Network decoupling: From regular to depthwise separable convolutions. arXiv preprintar Xiv:1808.05517"},{"issue":"8","key":"15837_CR7","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"key":"15837_CR8","unstructured":"Howard AG, Zhu M, Chen B, Kalenichenko D, Wang W, Weyand T, Andreetto M, Adam H (2017) Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861"},{"key":"15837_CR9","doi-asserted-by":"crossref","unstructured":"Howard A, Sandler M (2019) Searching for mobilenetv3. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 1314\u20131324","DOI":"10.1109\/ICCV.2019.00140"},{"key":"15837_CR10","doi-asserted-by":"crossref","unstructured":"Hurt\u00f3s N, Palomeras N, Nagappa S, Salvi J (2013) Automatic detection of underwater chain links using a forward-looking sonar. In 2013 MTS\/IEEE OCEANS-Bergen, pp 1\u20137","DOI":"10.1109\/OCEANS-Bergen.2013.6608106"},{"key":"15837_CR11","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"15837_CR12","doi-asserted-by":"publisher","first-page":"1890","DOI":"10.1109\/TIP.2019.2946469","volume":"29","author":"K Hu","year":"2019","unstructured":"Hu K, Wang Z (2019) Graph sequence recurrent neural network for vision-based freezing of gait detection. IEEE Trans Image Process 29:1890\u20131901","journal-title":"IEEE Trans Image Process"},{"key":"15837_CR13","doi-asserted-by":"crossref","unstructured":"Jiang Z, Liu Y, Yang C (2020) Learning where to focus for efficient video object detection. In European Conference on Computer Vision, pp 18\u201334","DOI":"10.1007\/978-3-030-58517-4_2"},{"key":"15837_CR14","doi-asserted-by":"crossref","unstructured":"Kim J, Yu S-C (2016) Convolutional neural network-based real-time rov detection using forward-looking sonar image. In 2016 IEEE\/OES Autonomous Underwater Vehicles (AUV), pp 396\u2013400","DOI":"10.1109\/AUV.2016.7778702"},{"key":"15837_CR15","first-page":"1097","volume":"25","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. Adv Neural Inf Process Syst 25:1097\u20131105","journal-title":"Adv Neural Inf Process Syst"},{"key":"15837_CR16","unstructured":"Liu M, Zhu M (2018) Mobile video object detection with temporally-aware feature maps. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5686\u20135695"},{"issue":"3","key":"15837_CR17","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1007\/s12555-019-0690-4","volume":"18","author":"T Maki","year":"2020","unstructured":"Maki T, Horimoto H (2020) Tracking a sea turtle by an auv with a multibeam imaging sonar: Toward robotic observation of marine life. Int J Control Autom Syst 18(3):597\u2013604","journal-title":"Int J Control Autom Syst"},{"key":"15837_CR18","doi-asserted-by":"crossref","unstructured":"Ma Q, Jiang L, Yu W (2020) Training with noise adversarial network: A generalization method for object detection on sonar image. In Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp 729\u2013738","DOI":"10.1109\/WACV45572.2020.9093467"},{"key":"15837_CR19","unstructured":"McKay J, Gerg I, Monga V, Raj RG (2017) What\u2019s mine is yours: Pretrained cnns for limited training sonar atr. In OCEANS 2017-Anchorage, pp 1\u20137"},{"issue":"7","key":"15837_CR20","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1109\/LSP.2010.2051574","volume":"17","author":"V Myers","year":"2010","unstructured":"Myers V, Fawcett J (2010) A template matching procedure for automatic target recognition in synthetic aperture sonar imagery. IEEE Signal Process Lett 17(7):683\u2013686","journal-title":"IEEE Signal Process Lett"},{"issue":"6","key":"15837_CR21","doi-asserted-by":"publisher","first-page":"1933","DOI":"10.3390\/s21061933","volume":"21","author":"R Qin","year":"2021","unstructured":"Qin R, Zhao X, Zhu W (2021) Multiple receptive field network (mrf-net) for autonomous underwater vehicle fishing net detection using forward-looking sonar images. Sensors 21(6):1933","journal-title":"Sensors"},{"issue":"3","key":"15837_CR22","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1007\/s12555-019-0691-3","volume":"18","author":"M Sung","year":"2020","unstructured":"Sung M, Kim J, Lee M (2020) Realistic sonar image simulation using deep learning for underwater object detection. Int J Control Autom Syst 18(3):523\u2013534","journal-title":"Int J Control Autom Syst"},{"key":"15837_CR23","first-page":"032045","volume":"1237","author":"M Tian","year":"2019","unstructured":"Tian M, Chen H, Wang Q (2019) Detection and recognition of flower image based on ssd network in video stream. J Physics: Conf Ser 1237:032045","journal-title":"J Physics: Conf Ser"},{"key":"15837_CR24","doi-asserted-by":"crossref","unstructured":"Valdenegro-Toro M (2016) Objectness scoring and detection proposals in forward-looking sonar images with convolutional neural networks. In IAPR workshop on artificial neural networks in pattern recognition, pp 209\u2013219","DOI":"10.1007\/978-3-319-46182-3_18"},{"key":"15837_CR25","doi-asserted-by":"crossref","unstructured":"Wang C-Y, Bochkovskiy A, Liao H-YM (2022) Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. arXiv preprintar Xiv:2207.02696","DOI":"10.1109\/CVPR52729.2023.00721"},{"key":"15837_CR26","doi-asserted-by":"crossref","unstructured":"Wang Y-X, Girshick R, Hebert M, Hariharan B (2018) Low-shot learning from imaginary data. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7278\u20137286","DOI":"10.1109\/CVPR.2018.00760"},{"issue":"2","key":"15837_CR27","doi-asserted-by":"publisher","first-page":"1509","DOI":"10.1109\/JSEN.2021.3131645","volume":"22","author":"Z Wang","year":"2022","unstructured":"Wang Z, Zhang S, Huang W, Guo J, Zeng L (2022) Sonar image target detection based on adaptive global feature enhancement network. IEEE Sens J 22(2):1509\u20131530","journal-title":"IEEE Sens J"},{"issue":"10","key":"15837_CR28","doi-asserted-by":"publisher","first-page":"6284","DOI":"10.1109\/TGRS.2013.2295843","volume":"52","author":"DP Williams","year":"2014","unstructured":"Williams DP, Fakiris E (2014) Exploiting environmental information for improved underwater target classification in sonar imagery. IEEE Trans Geosci Remote Sens 52(10):6284\u20136297","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"6","key":"15837_CR29","doi-asserted-by":"publisher","first-page":"063030","DOI":"10.1117\/1.JEI.31.6.063030","volume":"31","author":"S Wu","year":"2022","unstructured":"Wu S, Liu Y, Li S, Zhang S (2022) Lsh-detr: object detection algorithm for marine benthic organisms based on improved detr. J Electron Imaging 31(6):063030","journal-title":"J Electron Imaging"},{"key":"15837_CR30","doi-asserted-by":"crossref","unstructured":"Zacchini L, Topini A, Franchi M, Secciani N, Manzari V, Bazzarello L, Stifani M, Ridolfi A (2022) Autonomous underwater environment perceiving and modeling: An experimental campaign with feelhippo auv for forward looking sonar-based automatic target recognition and data association. IEEE Journal of Oceanic Engineering, pp 1\u201320","DOI":"10.1109\/JOE.2022.3209719"},{"key":"15837_CR31","first-page":"1","volume":"60","author":"T Zhou","year":"2022","unstructured":"Zhou T, Si J, Wang L, Xu C, Yu X (2022) Automatic detection of underwater small targets using forward-looking sonar images. IEEE Trans Geosci Remote Sens 60:1\u201312","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"15837_CR32","doi-asserted-by":"crossref","unstructured":"Zhou W, Wang Z (2021) Research on autonomous detection method of underwater unmanned vehicle. In 2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), pp 1\u20135","DOI":"10.1109\/ICSPCC52875.2021.9564748"},{"key":"15837_CR33","doi-asserted-by":"crossref","unstructured":"Zhu X, Xiong Y (2017) Deep feature flow for video recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2349\u20132358","DOI":"10.1109\/CVPR.2017.441"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15837-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-15837-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15837-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T09:13:49Z","timestamp":1704878029000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-15837-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,20]]},"references-count":33,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["15837"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-15837-5","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,20]]},"assertion":[{"value":"21 October 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 March 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 May 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 June 2023","order":4,"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 that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}