{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:50:15Z","timestamp":1743144615628,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030578800"},{"type":"electronic","value":"9783030578817"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-57881-7_40","type":"book-chapter","created":{"date-parts":[[2020,8,31]],"date-time":"2020-08-31T14:04:16Z","timestamp":1598882656000},"page":"451-462","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Video Action Recognition Based on Hybrid Convolutional Network"],"prefix":"10.1007","author":[{"given":"Yanyan","family":"Song","sequence":"first","affiliation":[]},{"given":"Li","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Lina","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Xinyue","family":"Lv","sequence":"additional","affiliation":[]},{"given":"Zihao","family":"Ma","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,1]]},"reference":[{"key":"40_CR1","unstructured":"Simonyan, K., Zisserman, A.: Two-stream convolutional networks for action recognition in videos. In: Computer Vision and Pattern Recognition (2014)"},{"key":"40_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1007\/978-3-319-46484-8_2","volume-title":"Computer Vision \u2013 ECCV 2016","author":"L Wang","year":"2016","unstructured":"Wang, L., et al.: Temporal segment networks: towards good practices for deep action recognition. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9912, pp. 20\u201336. Springer, Cham (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-319-46484-8_2"},{"key":"40_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1007\/978-3-030-01246-5_49","volume-title":"Computer Vision \u2013 ECCV 2018","author":"B Zhou","year":"2018","unstructured":"Zhou, B., Andonian, A., Oliva, A., Torralba, A.: Temporal relational reasoning in videos. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11205, pp. 831\u2013846. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-030-01246-5_49"},{"key":"40_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1007\/978-3-030-20893-6_23","volume-title":"Computer Vision \u2013 ACCV 2018","author":"Y Zhu","year":"2019","unstructured":"Zhu, Y., Lan, Z., Newsam, S., Hauptmann, A.: Hidden two-stream convolutional networks for action recognition. In: Jawahar, C.V., Li, H., Mori, G., Schindler, K. (eds.) ACCV 2018. LNCS, vol. 11363, pp. 363\u2013378. Springer, Cham (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-20893-6_23"},{"key":"40_CR5","doi-asserted-by":"crossref","unstructured":"Tran, D., Bourdev, L., Fergus, R., et al.: Learning spatiotemporal features with 3D convolutional networks. In: IEEE International Conference on Computer Vision, Santiago, pp. 4489\u20134497. IEEE Computer Society (2015)","DOI":"10.1109\/ICCV.2015.510"},{"key":"40_CR6","unstructured":"Diba, A., Fayyaz, M., Sharma, V., et al.: Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification. Computing Research Repository (2017)"},{"key":"40_CR7","doi-asserted-by":"crossref","unstructured":"Carreira, J., Zisserman, A.: Quo Vadis, action recognition? A new model and the kinetics dataset. In: IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, pp. 4724\u20134733. IEEE Computer Society (2017)","DOI":"10.1109\/CVPR.2017.502"},{"issue":"1","key":"40_CR8","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1109\/TPAMI.2012.59","volume":"35","author":"S Ji","year":"2013","unstructured":"Ji, S., Xu, W., Yang, M., Yu, K.: 3D convolutional neural networks for human action recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35(1), 221\u2013231 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"40_CR9","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., et al.: Deep residual learning for image recognition. CoRR abs\/1512.03385 (2015)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"8","key":"40_CR10","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.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"40_CR11","unstructured":"Vaswani, A., et al.: Attention is all you need. CoRR abs\/1706.03762 (2017)"},{"key":"40_CR12","unstructured":"Soomro, K., Zamir, A.R., Shah, M.: UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild. CoRR abs\/1212.0402 (2012)"},{"key":"40_CR13","doi-asserted-by":"crossref","unstructured":"Hara, K., Kataoka, H., Satoh, Y.: Can spatiotemporal 3D CNNs retrace the history of 2D CNNs and ImageNet? In: IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, pp. 6546\u20136555. IEEE Computer Society (2018)","DOI":"10.1109\/CVPR.2018.00685"},{"key":"40_CR14","doi-asserted-by":"crossref","unstructured":"Tran, D., Wang, H., Torresani, L., et al.: A closer look at spatiotemporal convolutions for action recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, pp. 6450\u20136459. IEEE Computer Society (2018)","DOI":"10.1109\/CVPR.2018.00675"},{"issue":"2","key":"40_CR15","doi-asserted-by":"publisher","first-page":"1877","DOI":"10.1007\/s11063-018-09972-6","volume":"50","author":"Z Liu","year":"2019","unstructured":"Liu, Z., Hu, H., Zhang, J.: Spatiotemporal fusion networks for video action recognition. Neural Process. Lett. 50(2), 1877\u20131890 (2019). \nhttps:\/\/doi.org\/10.1007\/s11063-018-09972-6","journal-title":"Neural Process. Lett."},{"key":"40_CR16","doi-asserted-by":"crossref","unstructured":"Li, Q., Qiu, Z., Yao, T., et al.: Action recognition by learning deep multi-granular spatio-temporal video representation. In: International Conference on Multimedia Retrieval, pp. 159\u2013166. ACM, New York (2016)","DOI":"10.1145\/2911996.2912001"},{"key":"40_CR17","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Sun, X., Zha, Z.-J., Zeng, W.: MiCT: mixed 3D\/2D convolutional tube for human action recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, pp. 449\u2013458. IEEE Computer Society (2018)","DOI":"10.1109\/CVPR.2018.00054"},{"issue":"10","key":"40_CR18","first-page":"3030","volume":"40","author":"W Yu","year":"2019","unstructured":"Yu, W., Wei, Y., Li, L.: Human behavior recognition model based on multi-model fusion. Comput. Eng. Des. 40(10), 3030\u20133036 (2019)","journal-title":"Comput. Eng. Des."},{"issue":"19","key":"40_CR19","first-page":"37","volume":"42","author":"M Zeng","year":"2019","unstructured":"Zeng, M., Zheng, Z., Luo, S.: Dual-convolution human behavior recognition combined with LSTM. Modern Electron. Tech. 42(19), 37\u201340 (2019)","journal-title":"Modern Electron. Tech."},{"issue":"09","key":"40_CR20","first-page":"2631","volume":"40","author":"C Ma","year":"2019","unstructured":"Ma, C., Mao, Z., Cui, J., Yi, W.: Behavior recognition based on deep LSTM and dual stream convergence network. Comput. Eng. Des. 40(09), 2631\u20132637 (2019)","journal-title":"Comput. Eng. Des."},{"issue":"09","key":"40_CR21","first-page":"106","volume":"46","author":"L Ma","year":"2019","unstructured":"Ma, L., Yu, W., Zhu, Y., Wang, C., Wang, P.: Recognition of fall behavior based on deep learning. Comput. Sci. 46(09), 106\u2013112 (2019)","journal-title":"Comput. Sci."},{"issue":"14","key":"40_CR22","doi-asserted-by":"publisher","first-page":"3160","DOI":"10.3390\/s19143160","volume":"19","author":"I Rodr\u00edguez-Moreno","year":"2019","unstructured":"Rodr\u00edguez-Moreno, I., Mart\u00ednez-Otzeta, J.M., Sierra, B., Rodriguez, I., Jauregi, E.: Video activity recognition: state-of-the-art. Sensors (Basel, Switzerland) 19(14), 3160 (2019)","journal-title":"Sensors (Basel, Switzerland)"},{"key":"40_CR23","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1093\/nar\/gkl923","volume":"35","author":"DS Wishart","year":"2007","unstructured":"Wishart, D.S., Tzur, D., et al.: HMDB: the human metabolome database. Nucleic Acids Res. 35, 521\u2013526 (2007)","journal-title":"Nucleic Acids Res."},{"issue":"2","key":"40_CR24","doi-asserted-by":"publisher","first-page":"535","DOI":"10.32604\/cmc.2019.07948","volume":"61","author":"SMS Shah","year":"2019","unstructured":"Shah, S.M.S., Malik, T.A., Khatoon, R., Hassan, S.S., Shah, F.A.: Human behavior classification using geometrical features of skeleton and support vector machines. Comput. Mater. Continua 61(2), 535\u2013553 (2019)","journal-title":"Comput. Mater. Continua"},{"issue":"2","key":"40_CR25","doi-asserted-by":"publisher","first-page":"569","DOI":"10.32604\/cmc.2019.05952","volume":"61","author":"K Yang","year":"2019","unstructured":"Yang, K., Wang, Y., Zhang, W., Yao, J., Le, Y.: Keyphrase generation based on self-attention mechanism. Comput. Mater. Continua 61(2), 569\u2013581 (2019)","journal-title":"Comput. Mater. Continua"},{"issue":"3","key":"40_CR26","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.32604\/cmc.2019.06361","volume":"61","author":"W Song","year":"2019","unstructured":"Song, W., Yu, J., Zhao, X., Wang, A.: Research on action recognition and content analysis in videos based on DNN and MLN. Comput. Mater. Continua 61(3), 1189\u20131204 (2019)","journal-title":"Comput. Mater. Continua"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence and Security"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-57881-7_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,31]],"date-time":"2020-08-31T14:34:26Z","timestamp":1598884466000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-57881-7_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030578800","9783030578817"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-57881-7_40","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"1 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICAIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence and Security","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hohhot","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 July 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 July 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"incodldos2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icaisconf.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}