{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T14:29:13Z","timestamp":1782484153655,"version":"3.54.5"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"20","license":[{"start":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:00:00Z","timestamp":1625616000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:00:00Z","timestamp":1625616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Exercise prescription for compulsory isolation of drug addicts based on data intelligence Accurate recommendation system development","award":["201903D321039"],"award-info":[{"award-number":["201903D321039"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1007\/s00521-021-06151-y","type":"journal-article","created":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T06:02:36Z","timestamp":1625637756000},"page":"14627-14639","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Analysis and design of dual-feature fusion neural network for sports injury estimation model"],"prefix":"10.1007","volume":"35","author":[{"given":"Linsheng","family":"Meng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Endong","family":"Qiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,7,7]]},"reference":[{"issue":"1","key":"6151_CR1","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1136\/bjsm.37.1.13","volume":"37","author":"DF Murphy","year":"2003","unstructured":"Murphy DF, Connolly DAJ, Beynnon B (2003) Risk factors for lower extremity injury: a review of the literature. Br J Sports Med 37(1):13\u201329","journal-title":"Br J Sports Med"},{"issue":"5","key":"6151_CR2","doi-asserted-by":"publisher","first-page":"1091","DOI":"10.1166\/jmihi.2020.2892","volume":"10","author":"H Ba","year":"2020","unstructured":"Ba H (2020) Medical sports rehabilitation deep learning system of sports injury based on MRI image analysis. J Med Imaging Health Informatics 10(5):1091\u20131097","journal-title":"J Med Imaging Health Informatics"},{"issue":"1","key":"6151_CR3","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1136\/bjsports-2019-101772","volume":"55","author":"D Palmer","year":"2021","unstructured":"Palmer D, Cooper DJ, Emery C, Batt ME, Engebretsen L, Scammell BE, Budgett R (2021) Self-reported sports injuries and later-life health status in 3357 retired Olympians from 131 countries: a cross-sectional survey among those competing in the games between London 1948 and PyeongChang 2018. Br J Sports Med 55(1):46\u201353","journal-title":"Br J Sports Med"},{"key":"6151_CR4","doi-asserted-by":"crossref","unstructured":"Sillero-Quintana M, Gomez-Carmona PM, Fern\u00e1ndez-Cuevas I (2021) Infrared thermography as a means of monitoring and preventing sports injuries. In: Research anthology on business strategies, health factors, and ethical implications in sports and eSports. IGI Global, pp 832\u2013865","DOI":"10.4018\/978-1-7998-7707-3.ch046"},{"issue":"1","key":"6151_CR5","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.fcl.2020.12.001","volume":"26","author":"WA Davis 3rd","year":"2021","unstructured":"Davis WA 3rd, Yagnik GP (2021) In-season management of acute and subacute sports foot injuries. Foot Ankle Clin 26(1):187\u2013203","journal-title":"Foot Ankle Clin"},{"issue":"10","key":"6151_CR6","doi-asserted-by":"publisher","first-page":"2227","DOI":"10.1007\/s40279-018-0953-x","volume":"48","author":"C Bolling","year":"2018","unstructured":"Bolling C, Van Mechelen W, Pasman HR, Verhagen E (2018) Context matters: revisiting the first step of the \u2018sequence of prevention\u2019of sports injuries. Sports Med 48(10):2227\u20132234","journal-title":"Sports Med"},{"key":"6151_CR7","doi-asserted-by":"crossref","unstructured":"Andreoli CV, Chiaramonti BC, Biruel E, de Castro Pochini A, Ejnisman B, Cohen M (2018). Epidemiology of sports injuries in basketball: integrative systematic review. BMJ Open Sport & Exercise Med 4(1).","DOI":"10.1136\/bmjsem-2018-000468"},{"issue":"6","key":"6151_CR8","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1007\/s10278-019-00193-4","volume":"32","author":"PD Chang","year":"2019","unstructured":"Chang PD, Wong TT, Rasiej MJ (2019) Deep learning for detection of complete anterior cruciate ligament tear. J Digit Imaging 32(6):980\u2013986","journal-title":"J Digit Imaging"},{"key":"6151_CR9","doi-asserted-by":"crossref","unstructured":"Ning X, Gong K, Li W, Zhang L, Bai X, Tian S (2020) Feature Refinement and Filter Network for Person Re-identification. IEEE Trans Circuits Syst Video Technol.","DOI":"10.1109\/TCSVT.2020.3043026"},{"key":"6151_CR10","doi-asserted-by":"crossref","unstructured":"Jan MA, Khan F, Mastorakis S, Adil M, Akbar A, Stergiou N (2021) LightIoT: Lightweight and secure communication for energy-efficient IoT in health informatics.\u00a0IEEE Trans Green Commun Netw,  pp 1\u201310.","DOI":"10.1109\/TGCN.2021.3077318"},{"key":"6151_CR11","doi-asserted-by":"publisher","first-page":"1944","DOI":"10.1109\/LSP.2020.3032277","volume":"27","author":"X Ning","year":"2020","unstructured":"Ning X, Duan P, Li W, Zhang S (2020) Real-time 3D face alignment using an Encoder-Decoder Network with an efficient ddeconvolution layer. IEEE Signal Process Lett 27:1944\u20131948","journal-title":"IEEE Signal Process Lett"},{"key":"6151_CR12","doi-asserted-by":"crossref","unstructured":"Liu Q (2021) Aerobics posture recognition based on neural network and sensors.\u00a0Neural Comput Applications, pp 1\u201312.","DOI":"10.1007\/s00521-020-05632-w"},{"key":"6151_CR13","doi-asserted-by":"crossref","unstructured":"Ning X, Gong K, Li W, Zhang L (2020) JWSAA: Joint weak saliency and attention aware for person re-identification. Neurocomputing.","DOI":"10.1016\/j.neucom.2020.05.106"},{"key":"6151_CR14","doi-asserted-by":"crossref","unstructured":"Cai  W, Liu B, Wei Z, Li M, Kan J (2021) TARDB-Net: triple-attention guided residual dense and BiLSTM networks for hyperspectral image classification.\u00a0Multimedia Tools Applications,  pp 1\u201322.","DOI":"10.1007\/s11042-020-10188-x"},{"issue":"1","key":"6151_CR15","doi-asserted-by":"publisher","first-page":"9","DOI":"10.52810\/TPRIS.2021.100009","volume":"1","author":"X Ning","year":"2021","unstructured":"Ning X, Wang Y, Tian W, Liu L, Cai W (2021) A bbiomimetic covering learning method based on principle of homology continuity. ASP Trans Pattern Recogn Intell Syst 1(1):9\u201316","journal-title":"ASP Trans Pattern Recogn Intell Syst"},{"issue":"2","key":"6151_CR16","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/MNET.011.2000303","volume":"35","author":"Q Liu","year":"2021","unstructured":"Liu Q, Cheng L, Jia AL, Liu C (2021) Deep reinforcement learning for communication flow control in wireless mesh networks. IEEE Network 35(2):112\u2013119","journal-title":"IEEE Network"},{"key":"6151_CR17","doi-asserted-by":"crossref","unstructured":"Liu R, Ning X, Cai W,  Li G (2021) Multiscale dense cross-attention mechanism with covariance pooling for hyperspectral image scene classification. Mobile Information Syst.","DOI":"10.1155\/2021\/9962057"},{"key":"6151_CR18","doi-asserted-by":"publisher","unstructured":"Jianming\u00a0Zhang,\u00a0Juan\u00a0Sun,\u00a0Jin\u00a0Wang,\u00a0Xiao-Guang\u00a0Yue (2020)\u00a0Visual\u00a0object\u00a0tracking\u00a0based\u00a0on\u00a0residual\u00a0network\u00a0and\u00a0cascaded\u00a0correlation\u00a0filters.\u00a0J\u00a0Ambient\u00a0Intell\u00a0Humanized\u00a0Comput. \u00a0https:\/\/doi.org\/10.1007\/s12652-020-02572-0.","DOI":"10.1007\/s12652-020-02572-0"},{"key":"6151_CR19","doi-asserted-by":"crossref","unstructured":"Ning X,\u00a0Wang X,\u00a0Xu S,\u00a0Cai W, Zhang L, Yu L, Li W (2021)\u00a0A review of research on co-training.\u00a0Concurrency and computation: practice and experience, 2021.","DOI":"10.1002\/cpe.6276"},{"issue":"1","key":"6151_CR20","doi-asserted-by":"publisher","first-page":"67","DOI":"10.3390\/rs9010067","volume":"9","author":"Y Li","year":"2017","unstructured":"Li Y, Zhang H, Shen Q (2017) Spectral\u2013spatial classification of hyperspectral imagery with 3D convolutional neural network. Remote Sensing 9(1):67","journal-title":"Remote Sensing"},{"issue":"6","key":"6151_CR21","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2017) ImageNet classification with deep convolutional neural networks. Commun ACM 60(6):84\u201390","journal-title":"Commun ACM"},{"key":"6151_CR22","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition\u00a0(pp. 770\u2013778).","DOI":"10.1109\/CVPR.2016.90"},{"key":"6151_CR23","doi-asserted-by":"crossref","unstructured":"Huang G, Liu Z, Van Der Maaten L, Weinberger KQ (2017) Densely connected convolutional networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4700\u20134708.","DOI":"10.1109\/CVPR.2017.243"},{"key":"6151_CR24","doi-asserted-by":"crossref","unstructured":"Zhang C, Li G, Du S, Tan W, Gao F (2019) Three-dimensional densely connected convolutional network for hyperspectral remote sensing image classification. J Appl Remote Sensing 13(1):016519.","DOI":"10.1117\/1.JRS.13.016519"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06151-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-06151-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06151-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T09:52:20Z","timestamp":1685699540000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-06151-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,7]]},"references-count":24,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["6151"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-06151-y","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,7]]},"assertion":[{"value":"10 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 July 2021","order":3,"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 no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}