{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T04:13:07Z","timestamp":1775707987786,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2023,12,27]],"date-time":"2023-12-27T00:00:00Z","timestamp":1703635200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,27]],"date-time":"2023-12-27T00:00:00Z","timestamp":1703635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 62032013"],"award-info":[{"award-number":["No. 62032013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["No. N2324004-12"],"award-info":[{"award-number":["No. N2324004-12"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1007\/s00521-023-09342-x","type":"journal-article","created":{"date-parts":[[2023,12,27]],"date-time":"2023-12-27T22:02:36Z","timestamp":1703714556000},"page":"5217-5230","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Attention-based deep supervised hashing for near duplicate video retrieval"],"prefix":"10.1007","volume":"36","author":[{"given":"Naifei","family":"Shi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4549-744X","authenticated-orcid":false,"given":"Chong","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Tie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenchao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingwei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chiu-Wing","family":"Sham","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,27]]},"reference":[{"key":"9342_CR1","doi-asserted-by":"crossref","unstructured":"Li M, Monga V (2015) Twofold video hashing with automatic synchronization. IEEE Trans Inf Forens Secur 10(8):1727\u20131738","DOI":"10.1109\/TIFS.2015.2425362"},{"key":"9342_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TKDE.2019.2937924","volume":"PP(99)","author":"X Nie","year":"2019","unstructured":"Nie X, Jing W, Cui C, Zhang J, Yin Y (2019) Joint multi-view hashing for large-scale near-duplicate video retrieval. IEEE Trans Knowl Data Eng 32(10):1951\u20131965","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9342_CR3","doi-asserted-by":"crossref","unstructured":"Zheng L, Lei Y, Qiu G, Huang J (2012) Near-duplicate image detection in a visually salient riemannian space. IEEE Trans Inf Forens Secur 7(5):1578\u20131593","DOI":"10.1109\/TIFS.2012.2206386"},{"issue":"1","key":"9342_CR4","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/TCSVT.2017.2776159","volume":"29","author":"F Khelifi","year":"2019","unstructured":"Khelifi F, Bouridane A (2019) Perceptual video hashing for content identification and authentication. IEEE Trans Circuits Syst Video Technol 29(1):50\u201367","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"9342_CR5","doi-asserted-by":"crossref","unstructured":"Liu X, Nie X, Dai Q, Huang Y, Lian L, Yin Y (2021) Reinforced short-length hashing. IEEE Trans Circuits Syst Video Technol 31(9):3655\u20133668","DOI":"10.1109\/TCSVT.2020.3040863"},{"key":"9342_CR6","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.asoc.2021.107467","volume":"109","author":"X Nie","year":"2021","unstructured":"Nie X, Zhou X, Shi Y, Sun J, Yin Y (2021) Classification-enhancement deep hashing for large-scale video retrieval. Appl Soft Comput 109:107467","journal-title":"Appl Soft Comput"},{"issue":"4","key":"9342_CR7","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1109\/TPAMI.2013.225","volume":"36","author":"J Masci","year":"2014","unstructured":"Masci J, Bronstein MM, Bronstein AM, Schmidhuber J (2014) Multimodal similarity-preserving hashing. IEEE Trans Pattern Anal Mach Intell 36(4):824\u2013830","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9342_CR8","doi-asserted-by":"crossref","unstructured":"Lin Z, Ding G, Hu M, Wang J (2015) Semantics-preserving hashing for cross-view retrieval. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3864\u20133872","DOI":"10.1109\/CVPR.2015.7299011"},{"issue":"6","key":"9342_CR9","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1109\/TSMCC.2011.2109710","volume":"41","author":"W Hu","year":"2011","unstructured":"Hu W, Xie N, Li L, Zeng X, Maybank S (2011) A survey on visual content-based video indexing and retrieval. IEEE Trans Syst, Man, Cybern, Part C (Appl Rev) 41(6):797\u2013819","journal-title":"IEEE Trans Syst, Man, Cybern, Part C (Appl Rev)"},{"issue":"1","key":"9342_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1126004.1126005","volume":"2","author":"MS Lew","year":"2006","unstructured":"Lew MS, Sebe N, Djeraba C, Jain R (2006) Content-based multimedia information retrieval: state of the art and challenges. ACM Trans Multimedia Comput Commun Appl 2(1):1\u201319","journal-title":"ACM Trans Multimedia Comput Commun Appl"},{"issue":"4","key":"9342_CR11","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1561\/1500000014","volume":"2","author":"C Snoek","year":"2009","unstructured":"Snoek C, Worring M (2009) Concept-based video retrieval. Found Trends Inf Retr 2(4):215\u2013322","journal-title":"Found Trends Inf Retr"},{"key":"9342_CR12","doi-asserted-by":"crossref","unstructured":"Song J, Yang Y, Huang Z, Shen HT, Hong R (2011) Multiple feature hashing for real-time large scale near-duplicate video retrieval. In: Proceedings of the 19th ACM international conference on Multimedia, pp 423\u2013432","DOI":"10.1145\/2072298.2072354"},{"key":"9342_CR13","doi-asserted-by":"crossref","unstructured":"Datar M, Immorlica N, Indyk P, Mirrokni V (2004) Locality sensitive hashing scheme based on p-stable distributions. In: Proceedings of the twentieth annual symposium on Computational geometry, pp 253\u2013262","DOI":"10.1145\/997817.997857"},{"issue":"12","key":"9342_CR14","doi-asserted-by":"publisher","first-page":"2916","DOI":"10.1109\/TPAMI.2012.193","volume":"35","author":"Y Gong","year":"2013","unstructured":"Gong Y, Lazebnik S, Gordo A, Perronnin F (2013) Iterative quantization: a procrustean approach to learning binary codes for large-scale image retrieval. IEEE Trans Pattern Anal Mach Intell 35(12):2916\u20132929","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9342_CR15","doi-asserted-by":"crossref","unstructured":"Wu G, Liu L, Guo Y, Ding G, Han J, Shen J, Shao L (2017) Unsupervised deep video hashing with balanced rotation. In: Proceedings of the 26th international joint conference on artificial intelligence, pp 3076\u20133082","DOI":"10.24963\/ijcai.2017\/429"},{"key":"9342_CR16","unstructured":"Weiss Y, Torralba A, Fergus R (2008) Spectral hashing. In: Advances in neural information processing systems 21"},{"key":"9342_CR17","doi-asserted-by":"crossref","unstructured":"Tang J, Li Z (2018) Weakly supervised multimodal hashing for scalable social image retrieval. IEEE Trans Circuits Syst Video Technol 28(10):2730\u20132741","DOI":"10.1109\/TCSVT.2017.2715227"},{"key":"9342_CR18","unstructured":"Yue C, Long M, Wang J, Han Z, Wen Q (2016) Deep quantization network for efficient image retrieval. In: Proceedings of the AAAI conference on artificial intelligence, pp 3457\u20133463"},{"key":"9342_CR19","doi-asserted-by":"crossref","unstructured":"Cao Z, Long M, Wang J, Yu PS (2017) Hashnet: deep learning to hash by continuation. In: Proceedings of the IEEE international conference on computer vision, pp 5608\u20135617","DOI":"10.1109\/ICCV.2017.598"},{"key":"9342_CR20","doi-asserted-by":"crossref","unstructured":"Liong VE, Lu J, Gang W, Moulin P, Jie Z (2015) Deep hashing for compact binary codes learning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2475\u20132483","DOI":"10.1109\/CVPR.2015.7298862"},{"key":"9342_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103762","volume":"123","author":"P Shan","year":"2020","unstructured":"Shan P, Wang Y, Fu C, Song W, Chen J (2020) Automatic skin lesion segmentation based on FC-DPN. Comput Biol Med 123:103762","journal-title":"Comput Biol Med"},{"issue":"3","key":"9342_CR22","doi-asserted-by":"publisher","first-page":"393","DOI":"10.3390\/bioengineering10030393","volume":"10","author":"T Zhao","year":"2023","unstructured":"Zhao T, Fu C, Tian Y, Song W, Sham CW (2023) GSN-HVNET: a lightweight, multi-task deep learning framework for nuclei segmentation and classification. Bioengineering 10(3):393","journal-title":"Bioengineering"},{"key":"9342_CR23","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, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"9342_CR24","doi-asserted-by":"crossref","unstructured":"Xia R, Pan Y, Lai H, Liu C, Yan S (2014) Supervised hashing for image retrieval via image representation learning. In: Proceedings of the AAAI conference on artificial intelligence, pp 2156\u20132162","DOI":"10.1609\/aaai.v28i1.8952"},{"key":"9342_CR25","first-page":"1","volume":"PP(6)","author":"VE Liong","year":"2017","unstructured":"Liong VE, Lu J, Tan YP, Zhou J (2017) Deep video hashing. IEEE Trans Multimedia 19(6): 1209\u20131219","journal-title":"IEEE Trans Multimedia"},{"issue":"9","key":"9342_CR26","doi-asserted-by":"publisher","first-page":"3094","DOI":"10.3390\/s21093094","volume":"21","author":"H Chen","year":"2021","unstructured":"Chen H, Hu C, Lee F, Lin C, Chen Q (2021) A supervised video hashing method based on a deep 3D convolutional neural network for large-scale video retrieval. Sensors 21(9):3094","journal-title":"Sensors"},{"issue":"7","key":"9342_CR27","doi-asserted-by":"publisher","first-page":"3210","DOI":"10.1109\/TIP.2018.2814344","volume":"27","author":"J Song","year":"2018","unstructured":"Song J, Zhang H, Li X, Gao L, Wang M, Hong R (2018) Self-supervised video hashing with hierarchical binary auto-encoder. IEEE Trans Image Process 27(7):3210\u20133221","journal-title":"IEEE Trans Image Process"},{"key":"9342_CR28","unstructured":"Li WJ, Wang S, Kang WC (2015) Feature learning based deep supervised hashing with pairwise labels. arXiv preprint arXiv:1511.03855"},{"key":"9342_CR29","doi-asserted-by":"crossref","unstructured":"Liu H, Wang R, Shan S, Chen X (2016) Deep supervised hashing for fast image retrieval. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2064\u20132072","DOI":"10.1109\/CVPR.2016.227"},{"key":"9342_CR30","unstructured":"Han Z, Long M, Wang J, Yue C (2016) Deep hashing network for efficient similarity retrieval. In: Proceedings of the AAAI conference on Artificial Intelligence, pp 2415\u20132421"},{"key":"9342_CR31","unstructured":"Krizhevsky A, Sutskever I, Hinton G (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems 25"},{"issue":"1","key":"9342_CR32","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1109\/TMM.2012.2199970","volume":"15","author":"P Li","year":"2013","unstructured":"Li P, Wang M, Cheng J, Xu C, Lu H (2013) Spectral hashing with semantically consistent graph for image indexing. IEEE Trans Multimedia 15(1):141\u2013152","journal-title":"IEEE Trans Multimedia"},{"key":"9342_CR33","doi-asserted-by":"crossref","unstructured":"Shen F, Shen C, Liu W, Shen HT (2015) Supervised discrete hashing. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 37\u201345","DOI":"10.1109\/CVPR.2015.7298598"},{"key":"9342_CR34","doi-asserted-by":"crossref","unstructured":"Wei L, Wang J, Ji R, Jiang YG, Chang SF (2012) Supervised hashing with kernels. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2074\u20132081","DOI":"10.1109\/CVPR.2012.6247912"},{"key":"9342_CR35","doi-asserted-by":"crossref","unstructured":"Yang E, Cheng D, Liu T, Wei L, Tao D (2018) Semantic structure-based unsupervised deep hashing. In: Proceedings of the 27th international joint conference on artificial intelligence, pp. 1064\u20131070","DOI":"10.24963\/ijcai.2018\/148"},{"key":"9342_CR36","first-page":"1","volume":"PP(99)","author":"F Shen","year":"2018","unstructured":"Shen F, Yan X, Li L, Yang Y, Shen HT (2018) Unsupervised deep hashing with similarity-adaptive and discrete optimization. IEEE Trans Pattern Anal Mach Intell 40(12):3034\u20133044","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9342_CR37","doi-asserted-by":"crossref","unstructured":"Jiang QY, Cui X, Li WJ (2018) Deep discrete supervised hashing. IEEE Trans Image Process 27(12):5996\u20136009","DOI":"10.1109\/TIP.2018.2864894"},{"key":"9342_CR38","doi-asserted-by":"crossref","unstructured":"Ye G, Dong L, Wang J, Chang SF (2013) Large-scale video hashing via structure learning. In: Proceedings of the IEEE international conference on computer vision, pp 2272\u20132279","DOI":"10.1109\/ICCV.2013.282"},{"key":"9342_CR39","doi-asserted-by":"crossref","unstructured":"Chen Z, Lu J, Feng J, Zhou J (2018) Nonlinear structural hashing for scalable video search. IEEE Trans Circuits Syst Video Technol 28(6):1421\u20131433","DOI":"10.1109\/TCSVT.2017.2669095"},{"key":"9342_CR40","doi-asserted-by":"crossref","unstructured":"Wu G, Li L, Guo Y, Ding G, Ling S (2017) Unsupervised deep video hashing with balanced rotation. In: Proceedings of the 26th international joint conference on artificial intelligence, pp 3076\u20133082","DOI":"10.24963\/ijcai.2017\/429"},{"issue":"4","key":"9342_CR41","doi-asserted-by":"publisher","first-page":"1993","DOI":"10.1109\/TIP.2018.2882155","volume":"28","author":"G Wu","year":"2018","unstructured":"Wu G, Han J, Guo Y, Li L, Ding G (2018) Unsupervised deep video hashing via balanced code for large-scale video retrieval. IEEE Trans Image Process 28(4):1993\u20132007","journal-title":"IEEE Trans Image Process"},{"key":"9342_CR42","doi-asserted-by":"crossref","unstructured":"Wang L, Xiong Y, Zhe W, Yu Q, Gool LV (2019) Temporal segment networks for action recognition in videos. IEEE Trans Pattern Anal Mach Intell 41(11):2740\u20132755","DOI":"10.1109\/TPAMI.2018.2868668"},{"key":"9342_CR43","doi-asserted-by":"crossref","unstructured":"Li S, Li X, Lu J, Zhou J (2021) Self-supervised video hashing via bidirectional transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 13549\u201313558","DOI":"10.1109\/CVPR46437.2021.01334"},{"key":"9342_CR44","doi-asserted-by":"crossref","unstructured":"Li Y, Ji B, Shi X, Zhang J, Kang B, Wang L (2020) Tea: Temporal excitation and aggregation for action recognition. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 909\u2013918","DOI":"10.1109\/CVPR42600.2020.00099"},{"key":"9342_CR45","doi-asserted-by":"crossref","unstructured":"Jiang B, Wang M, Gan W, Wu W, Yan J (2019) STM: Spatiotemporal and motion encoding for action recognition. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 2000\u20132009","DOI":"10.1109\/ICCV.2019.00209"},{"key":"9342_CR46","unstructured":"Soomro K, Zamir AR, Shah M (2012) UCF101: a dataset of 101 human actions classes from videos in the wild. arXiv preprint arXiv:1212.0402"},{"key":"9342_CR47","doi-asserted-by":"crossref","unstructured":"Kuehne H, Jhuang H, Garrote E, Poggio T, Serre T (2011) HMDB: a large video database for human motion recognition. In: IEEE international conference on computer vision","DOI":"10.1109\/ICCV.2011.6126543"},{"key":"9342_CR48","doi-asserted-by":"crossref","unstructured":"Jiang YG, Wu Z, Wang J, Xue X, Chang SF (2018). Exploiting feature and class relationships in video categorization with regularized deep neural networks. IEEE Trans Pattern Anal Mach Intell 40(2):352\u2013364","DOI":"10.1109\/TPAMI.2017.2670560"},{"key":"9342_CR49","doi-asserted-by":"crossref","unstructured":"Anuranji R, Srimathi H (2020) A supervised deep convolutional based bidirectional long short term memory video hashing for large scale video retrieval applications. Digit Signal Process 102:102729","DOI":"10.1016\/j.dsp.2020.102729"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09342-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-09342-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09342-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T21:56:13Z","timestamp":1709934973000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-09342-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,27]]},"references-count":49,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2024,4]]}},"alternative-id":["9342"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-09342-x","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,27]]},"assertion":[{"value":"25 March 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 2023","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 that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}