{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T01:52:43Z","timestamp":1743040363007,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030511029"},{"type":"electronic","value":"9783030511036"}],"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\/978-3-030-51103-6_11","type":"book-chapter","created":{"date-parts":[[2020,7,18]],"date-time":"2020-07-18T14:02:39Z","timestamp":1595080959000},"page":"124-136","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Design of Human-Computer Interactive Fire Extinguishing Training System Based on Virtual Reality Technology"],"prefix":"10.1007","author":[{"given":"Xue-yong","family":"Cui","sequence":"first","affiliation":[]},{"given":"Jun-qin","family":"Diao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,7,19]]},"reference":[{"issue":"3","key":"11_CR1","first-page":"866","volume":"38","author":"W Xin","year":"2018","unstructured":"Xin, W., Yun, Z., Chen, N., et al.: Image saliency detection via adaptive fusion of local and global sparse representation. J. Comput. Appl. 38(3), 866\u2013872 (2018)","journal-title":"J. Comput. Appl."},{"issue":"3","key":"11_CR2","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1109\/TPAMI.2014.2345401","volume":"37","author":"MM Cheng","year":"2015","unstructured":"Cheng, M.M., Mitra, N.J., Huang, X., et al.: Global contrast based salient region detection. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 569\u2013582 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"11_CR3","doi-asserted-by":"crossref","unstructured":"Jung, H.S., Kim, R.-C., Lee, S.-U.: A hierarchical synchronization technique based on the EREC for robust transmission of H.263 bit stream. IEEE Trans. Circ. Syst. Video Technol. 10(3), 433\u2013438 2000","DOI":"10.1109\/76.836289"},{"issue":"4","key":"11_CR4","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1109\/TCSVT.2013.2290579","volume":"24","author":"W Kim","year":"2014","unstructured":"Kim, W., Kim, C.: Spatiotemporal saliency detection using textural contrast and its applications. IEEE Trans. Circ. Syst. Video Technol. 24(4), 646\u2013659 (2014)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Yan, Q., Xu, L., Shi, J., et al.: Hierarchical saliency detection. In: CVPR 2013 Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, vol. 10, no. 153, pp. 1155\u20131162 (2013)","DOI":"10.1109\/CVPR.2013.153"},{"issue":"5","key":"11_CR6","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.infrared.2015.01.018","volume":"69","author":"X Wang","year":"2015","unstructured":"Wang, X., Ning, C., Xu, L.: Spatiotemporal saliency model for small moving object detection in infrared videos. Infrared Phys. Technol. 69(5), 111\u2013117 (2015)","journal-title":"Infrared Phys. Technol."},{"key":"11_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-46448-0_1","volume-title":"Computer Vision \u2013 ECCV 2016","author":"F Radenovi\u0107","year":"2016","unstructured":"Radenovi\u0107, F., Tolias, G., Chum, O.: CNN image retrieval learns from BoW: unsupervised fine-tuning with hard examples. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 3\u201320. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_1"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Azizpour, H., Razavian, A.S., Sullivan, J.: From generic to specific deep representations for visual recognition. In: Proceedings of the 2015 International Conference on Computer Vision and Pattern Recognition Workshops, vol. 6, no. 23, 36\u201345. IEEE Computer Society, Washington, DC (2015)","DOI":"10.1109\/CVPRW.2015.7301270"},{"issue":"3","key":"11_CR9","doi-asserted-by":"publisher","first-page":"251","DOI":"10.3169\/mta.4.251","volume":"4","author":"AS Razavian","year":"2016","unstructured":"Razavian, A.S., Sullivan, J., Carlsson, S.: Visual instance retrieval with deep convolutional networks. ITE Trans. Media Technol. Appl. 4(3), 251\u2013258 (2016)","journal-title":"ITE Trans. Media Technol. Appl."},{"issue":"10","key":"11_CR10","doi-asserted-by":"publisher","first-page":"1978","DOI":"10.1109\/TPAMI.2010.230","volume":"33","author":"L Wolf","year":"2011","unstructured":"Wolf, L., Hassner, T., Taigman, Y.: Effective unconstrained face recognition by combining multiple descriptors and learned background statistics. IEEE Trans. Pattern Anal. Mach. Intell. 33(10), 1978\u20131990 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"11_CR11","first-page":"842","volume":"38","author":"G Li","year":"2018","unstructured":"Li, G., Li, H., Shang, F., et al.: Noise image segmentation model with local intensity difference. J. Comput. Appl. 38(3), 842\u2013847 (2018)","journal-title":"J. Comput. Appl."},{"issue":"9","key":"11_CR12","first-page":"104","volume":"61","author":"S Niu","year":"2016","unstructured":"Niu, S., Chen, Q., Sisternes, L.D., et al.: Robust noise region-based active contour model via local similarity factor for image segmentation. Pattern Recogn. 61(9), 104\u2013119 (2016)","journal-title":"Pattern Recogn."},{"issue":"6","key":"11_CR13","first-page":"1327","volume":"36","author":"Z Jie-yu","year":"2014","unstructured":"Jie-yu, Z., Hong-ping, Z., Shu, C.: Face recognition based on weighted local binary pattern with adaptive threshold. J. Electron. Inf. Technol. 36(6), 1327\u20131333 (2014)","journal-title":"J. Electron. Inf. Technol."},{"issue":"11","key":"11_CR14","doi-asserted-by":"publisher","first-page":"2106","DOI":"10.1109\/TPAMI.2010.128","volume":"32","author":"I Naseem","year":"2010","unstructured":"Naseem, I., Togneri, R., Bennamoun, M.: Linear regression for face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 32(11), 2106\u20132112 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"9","key":"11_CR15","first-page":"2148","volume":"39","author":"JG Wu","year":"2017","unstructured":"Wu, J.G., Shao, T., Liu, Z.Y.: RGB-D saliency detection based on integration feature of color and depth saliency map. J. Electron. Inf. Technol. 39(9), 2148\u20132154 (2017)","journal-title":"J. Electron. Inf. Technol."},{"issue":"1","key":"11_CR16","first-page":"137","volume":"160","author":"NA Carlson","year":"2017","unstructured":"Carlson, N.A., Porter, J.R.: On the cardinality of Hausdorff spaces and H-closed spaces. Topol. Appl. 160(1), 137\u2013142 (2017)","journal-title":"Topol. Appl."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Multimedia Technology and Enhanced Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-51103-6_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T01:36:15Z","timestamp":1619228175000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-51103-6_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030511029","9783030511036"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-51103-6_11","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"19 July 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICMTEL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Multimedia Technology and Enhanced Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Leicester","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","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":"10 April 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icmtel2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/icmtel.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"confyplus","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"158","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":"83","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":"53% - 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":"3","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic all papers were presented in YouTubeLive.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}