{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T23:18:15Z","timestamp":1784071095256,"version":"3.55.0"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,1,3]],"date-time":"2022-01-03T00:00:00Z","timestamp":1641168000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,3]],"date-time":"2022-01-03T00:00:00Z","timestamp":1641168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1007\/s11760-021-02124-9","type":"journal-article","created":{"date-parts":[[2022,1,3]],"date-time":"2022-01-03T13:07:19Z","timestamp":1641215239000},"page":"1683-1690","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Drowning behavior detection in swimming pool based on deep learning"],"prefix":"10.1007","volume":"16","author":[{"given":"Fei","family":"Lei","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9013-1033","authenticated-orcid":false,"given":"Hengyu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feifei","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,1,3]]},"reference":[{"key":"2124_CR1","volume-title":"Preventing Drowning: An Implementation Guide","author":"D Meddings","year":"2017","unstructured":"Meddings, D., Altieri, E., Bierens, J., Cassell, E., Gissing, A., Guevarra, J.: Preventing Drowning: An Implementation Guide. World Health Organization, Oxford (2017)"},{"issue":"1","key":"2124_CR2","doi-asserted-by":"publisher","first-page":"44","DOI":"10.11622\/smedj.2017021","volume":"59","author":"J Chan","year":"2017","unstructured":"Chan, J., Ng, M., Ng, Y.: Drowning in swimming pools: clinical features and safety recommendations based on a study of descriptive records by emergency medical services attending to 995 calls. Singapore Med. J. 59(1), 44\u201349 (2017)","journal-title":"Singapore Med. J."},{"key":"2124_CR3","unstructured":"Ajil R., Srinivasan, K.: A novel drowning detection method for safety of swimmers. In: 2018 20th National Power Systems Conference (NPSC), pp. 1\u20136. IEEE (2018)"},{"key":"2124_CR4","unstructured":"Eng, H.L., Wang, J., Kam, A.H., Yau, W.Y.: Novel region-based modeling for human detection within highly dynamic aquatic environment. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR (2004)"},{"key":"2124_CR5","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.microc.2013.10.003","volume":"113","author":"J Bierens","year":"2014","unstructured":"Bierens, J., Scapigliati, A.: Drowning in swimming pools. Microchem. J. 113, 53\u201358 (2014)","journal-title":"Microchem. J."},{"issue":"8","key":"2124_CR6","first-page":"1","volume":"8","author":"N Salehi","year":"2016","unstructured":"Salehi, N., Keyvanara, M., Monadjemmi, S.A.: An automatic video-based drowning detection system for swimming pools using active contours. Int. J. Image Gr. Signal Process. 8(8), 1\u20138 (2016)","journal-title":"Int. J. Image Gr. Signal Process."},{"issue":"3","key":"2124_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2020.103535","volume":"80","author":"J Hou","year":"2021","unstructured":"Hou, J., Li, B.: Swimming target detection and tracking technology in video image processing. Microprocessors Microsyst. 80(3), 103535 (2021)","journal-title":"Microprocessors Microsyst."},{"key":"2124_CR8","doi-asserted-by":"crossref","unstructured":"Hayat, M.A., Yang, G., Iqbal, A., Saleem, A., Mateen, M.: The swimmers motion detection using improved vibe algorithm. In: 2019 International Conference on Robotics and Automation in Industry (ICRAI) (2019)","DOI":"10.1109\/ICRAI47710.2019.8967390"},{"key":"2124_CR9","doi-asserted-by":"crossref","unstructured":"Fei, L., Wang, X., Chen, D.: Drowning detection based on background subtraction. In: 2009 International Conference on Embedded Software and Systems (2009)","DOI":"10.1109\/ICESS.2009.35"},{"key":"2124_CR10","first-page":"1098","volume":"9","author":"DJ Huafu","year":"2020","unstructured":"Huafu, D.J., Cheng, T., Liu, B., Cheng, Z.S.: Research on iron surface crack detection algorithm based on improved yolov4 network. J. Phys. Conf. Ser. 9, 1098 (2020)","journal-title":"J. Phys. Conf. Ser."},{"key":"2124_CR11","doi-asserted-by":"crossref","unstructured":"Li, Y., Wang, H., Dang, L.M., Han, D., Moon, H.: A deep learning-based hybrid framework for object detection and recognition in autonomous driving. In: IEEE Access (2020)","DOI":"10.1109\/ACCESS.2020.3033289"},{"key":"2124_CR12","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.biosystemseng.2020.01.016","volume":"192","author":"A Yang","year":"2020","unstructured":"Yang, A., Huang, H., Zheng, B., Li, S., Xue, Y.: An automatic recognition framework for sow daily behaviours based on motion and image analyses. Biosys. Eng. 192, 56\u201371 (2020)","journal-title":"Biosys. Eng."},{"key":"2124_CR13","doi-asserted-by":"crossref","unstructured":"Kharrat, M., Wakuda, Y., Koshizuka, N., Sakamura, K.: Near drowning pattern recognition using neural network and wearable pressure and inertial sensors attached at swimmer\u2019s chest level. In: Mechatronics and Machine Vision in Practice (M2VIP), 2012 19th International Conference (2012)","DOI":"10.1145\/2398936.2398994"},{"key":"2124_CR14","doi-asserted-by":"crossref","unstructured":"Abdel, I.N., Alshbatat, S.A., Shamsa, A., Salama, A., Wadhha, A.: Automated vision-based surveillance system to detect drowning incidents in swimming pools. In: 2020 Advances in Science and Engineering Technology International Conferences (ASET), pp. 1\u20135 (2020)","DOI":"10.1109\/ASET48392.2020.9118248"},{"key":"2124_CR15","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.resuscitation.2020.09.022","volume":"156","author":"A Claesson","year":"2020","unstructured":"Claesson, A., Schierbeck, S., Hollenberg, J., Forsberg, S., Nord, A.: The use of drones and a machine-learning model for recognition of simulated drowning victims-a feasibility study. Resuscitation 156, 108 (2020)","journal-title":"Resuscitation"},{"key":"2124_CR16","doi-asserted-by":"crossref","unstructured":"Alotaibi, A.: Automated and intelligent system for monitoring swimming pool safety based on the IoT and transfer learning (2020)","DOI":"10.3390\/electronics9122082"},{"key":"2124_CR17","doi-asserted-by":"crossref","unstructured":"Morten, B., Jensen, R.G., Thomas, B.: Moeslund swimming pool occupancy analysis using deep learning on low quality video. In: Proceedings of the 1st International Workshop on Multimedia Content Analysis in Sports (2018)","DOI":"10.1145\/3265845.3265846"},{"key":"2124_CR18","doi-asserted-by":"crossref","unstructured":"Wang, F., Ai, Y., Zhang, W.: Detection of early dangerous state in deep water of indoor swimming pool based on surveillance video (2021)","DOI":"10.1007\/s11760-021-01953-y"},{"key":"2124_CR19","unstructured":"Bochkovskiy, A., Wang, C.Y., Hym L.: Yolov4: optimal speed and accuracy of object detection (2020)"},{"key":"2124_CR20","unstructured":"Redmon, J., Farhadi, A.: Yolov3: an incremental improvement. arXiv e-prints (2018)"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-02124-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-021-02124-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-02124-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T11:10:56Z","timestamp":1659093056000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-021-02124-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,3]]},"references-count":20,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["2124"],"URL":"https:\/\/doi.org\/10.1007\/s11760-021-02124-9","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,3]]},"assertion":[{"value":"29 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 December 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 January 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}