{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:16:37Z","timestamp":1743102997435,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031211607"},{"type":"electronic","value":"9783031211614"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-21161-4_53","type":"book-chapter","created":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T07:03:47Z","timestamp":1678259027000},"page":"695-708","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Real-Time Tracking Method of Students\u2019 Targets in Wushu Distance Teaching Based on Deep Learning"],"prefix":"10.1007","author":[{"given":"Jie","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Na","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,3,9]]},"reference":[{"key":"53_CR1","unstructured":"Feng, J., Zhao, H.: Dynamic nodes collaboration for target tracking in wireless sensor networks. IEEE Sens. J. 99, 1 (2021)"},{"key":"53_CR2","doi-asserted-by":"crossref","unstructured":"Gong, Y., Cui, C.: A measurement set partitioning algorithm based on CFSFDP for multiple extended target tracking in PHD Filter. Radioengineering, 30(2), 407\u2013416 (2021)","DOI":"10.13164\/re.2021.0407"},{"issue":"2","key":"53_CR3","first-page":"1","volume":"2021","author":"Z Li","year":"2021","unstructured":"Li, Z., Chen, X., Zha, Z.: Design of standoff cooperative target-tracking guidance laws for autonomous unmanned aerial vehicles. Math. Probl. Eng. 2021(2), 1\u201314 (2021)","journal-title":"Math. Probl. Eng."},{"issue":"2","key":"53_CR4","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1049\/cje.2020.00.156","volume":"31","author":"X Wang","year":"2022","unstructured":"Wang, X., Xie, W., Luo, J., et al.: Labeled multi-bernoulli maneuvering target tracking algorithm via TSK iterative regression model. Chin. J. Electron. 31(2), 227\u2013239 (2022)","journal-title":"Chin. J. Electron."},{"key":"53_CR5","doi-asserted-by":"crossref","unstructured":"Li, S., Feng, X., Deng, Z., et al.: Minimum error entropy based multiple model estimation for multisensor hybrid uncertain target tracking systems. IET Signal Processing, 14(3) (2020)","DOI":"10.1049\/iet-spr.2019.0178"},{"key":"53_CR6","doi-asserted-by":"crossref","unstructured":"Sun, C., Wan, Z., Huang, H., et al.: Intelligent target visual tracking and control strategy for open frame underwater vehicles. Robotica, 1\u201315 (2021)","DOI":"10.1017\/S0263574720001502"},{"key":"53_CR7","doi-asserted-by":"crossref","unstructured":"Ma, C., Huang, J.B., Yang, X., et al.: Hierarchical convolutional features for visual tracking. In: 2015 IEEE International Conference on Computer Vision (ICCV). IEEE Computer Society (2015)","DOI":"10.1109\/ICCV.2015.352"},{"key":"53_CR8","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. Comput. Sci. (2014)"},{"issue":"4","key":"53_CR9","doi-asserted-by":"publisher","first-page":"1424","DOI":"10.1109\/TIP.2015.2403231","volume":"24","author":"L Wang","year":"2015","unstructured":"Wang, L., Liu, T., Wang, G., et al.: Video tracking using learned hierarchical features. IEEE Trans. Image Process. 24(4), 1424\u20131435 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"53_CR10","doi-asserted-by":"crossref","unstructured":"Nam, H., Han, B.: Learming multi-domain convolutional neural networks for visual tracking (2015)","DOI":"10.1109\/CVPR.2016.465"},{"issue":"12","key":"53_CR11","first-page":"27","volume":"38","author":"C Tianhua","year":"2021","unstructured":"Tianhua, C., Siqun, Z., Yuxiao, L.: Semantic segmentation of remote sensing images based on improved deep neural network. Comput. Simul. 38(12), 27\u201332 (2021)","journal-title":"Comput. Simul."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","e-Learning, e-Education, and Online Training"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21161-4_53","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T07:40:01Z","timestamp":1678261201000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21161-4_53"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031211607","9783031211614"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21161-4_53","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"9 March 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"eLEOT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on E-Learning, E-Education, and Online Training","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Harbin","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eleot2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eleot.eai-conferences.org\/2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confyplus.eai.eu","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"226","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"111","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"49% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}