{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T17:27:01Z","timestamp":1775064421937,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"28-29","license":[{"start":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T00:00:00Z","timestamp":1601942400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T00:00:00Z","timestamp":1601942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"National Natural Science Foundation of Guangdong","award":["No.2018A030313994"],"award-info":[{"award-number":["No.2018A030313994"]}]},{"DOI":"10.13039\/501100004000","name":"Guangzhou Science and Technology Program key projects","doi-asserted-by":"publisher","award":["202002030298"],"award-info":[{"award-number":["202002030298"]}],"id":[{"id":"10.13039\/501100004000","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,11]]},"DOI":"10.1007\/s11042-020-09870-x","type":"journal-article","created":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T16:02:41Z","timestamp":1602000161000},"page":"35887-35901","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Video smoke detection base on dense optical flow and convolutional neural network"],"prefix":"10.1007","volume":"80","author":[{"given":"Yuanlu","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Wo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoqiang","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,6]]},"reference":[{"issue":"6","key":"9870_CR1","first-page":"992","volume":"46","author":"JZ Chen","year":"2016","unstructured":"Chen JZ et al (2016) Dynamic smoke detection using cascaded convolutional neural network for surveillance videos. J Univ Electron Sci Technol China 46(6):992\u2013996","journal-title":"J Univ Electron Sci Technol China"},{"key":"9870_CR2","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, et al. (2009) ImageNet: a Large-Scale Hierarchical Image Database. 2009 IEEE computer society conference on computer vision and pattern recognition (CVPR 2009), 20-25 June 2009, Miami, Florida, USA IEEE, 2009.","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"9870_CR3","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1007\/3-540-45103-X_50","volume":"2749","author":"G Farneback","year":"2003","unstructured":"Farneback G (2003) Two-frame motion estimation based on polynomial expansion. Scandinavian Conference on Image Analysis 2749:363\u2013370","journal-title":"Scandinavian Conference on Image Analysis"},{"key":"9870_CR4","doi-asserted-by":"crossref","unstructured":"Filonenko A, Kurnianggoro L, Jo K (2017) Comparative study of modern convolutional neural networks for smoke detection on image data. Proc. International Conference on Human System Interactions (HSI). pp. 64\u201368","DOI":"10.1109\/HSI.2017.8004998"},{"issue":"3","key":"9870_CR5","doi-asserted-by":"publisher","first-page":"566","DOI":"10.1109\/TMM.2019.2893549","volume":"21","author":"S Garg","year":"2019","unstructured":"Garg S, Kaur K, Kumar N, Rodrigues JJPC (2019) Hybrid deep-learning-based anomaly detection scheme for suspicious flow detection in SDN: a social multimedia perspective. IEEE Transactions on Multimedia 21(3):566\u2013578","journal-title":"IEEE Transactions on Multimedia"},{"issue":"3","key":"9870_CR6","doi-asserted-by":"publisher","first-page":"924","DOI":"10.1109\/TNSM.2019.2927886","volume":"16","author":"S Garg","year":"2019","unstructured":"Garg S, Kaur K, Kumar N, Kaddoum G, Zomaya AY, Ranjan R (2019) A hybrid deep learning-based model for anomaly detection in cloud datacenter networks. IEEE Trans Netw Serv Manag 16(3):924\u2013935","journal-title":"IEEE Trans Netw Serv Manag"},{"key":"9870_CR7","doi-asserted-by":"crossref","unstructured":"He KM, Zhang XY, Ren SQ, et al. (2016) Deep residual learning for image recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) IEEE Computer Society, 2016.","DOI":"10.1109\/CVPR.2016.90"},{"key":"9870_CR8","doi-asserted-by":"publisher","first-page":"29283","DOI":"10.1007\/s11042-018-5978-5","volume":"77","author":"YC Hu","year":"2018","unstructured":"Hu YC, Lu XB (2018) Real-time video fire smoke detection by utilizing spatial-temporal ConvNet features. Multimedia Tools and Applications 77:29283\u201329301","journal-title":"Multimedia Tools and Applications"},{"key":"9870_CR9","unstructured":"Ioffe S, Szegedy C (2015) Batch normalization: Accelerating deep network training by reducing internal covariate shift. Proceedings of the 32nd International Conference on International Conference on Machine Learning, vol. 37"},{"key":"9870_CR10","unstructured":"Kaiser T (2000) Fire detection with temperature sensor arrays. Security Technology, 2000. Proceedings. IEEE 34th Annual 2000 International Carnahan Conference on IEEE"},{"issue":"6","key":"9870_CR11","doi-asserted-by":"publisher","first-page":"9237","DOI":"10.1109\/JIOT.2019.2896120","volume":"6","author":"S Khan","year":"2019","unstructured":"Khan S, Muhammad K, Mumtaz S, Baik SW, de Albuquerque VHC (2019) Energy-efficient deep CNN for smoke detection in foggy IoT environment. IEEE Internet Things J 6(6):9237\u20139245","journal-title":"IEEE Internet Things J"},{"key":"9870_CR12","unstructured":"Kingma DP, Ba J (2015) Adam: a method for stochastic optimization. International Conference on Learning Representations"},{"key":"9870_CR13","unstructured":"Krizhevsky A, Sutskever I, Hinton G (2012) Imagenet classification with deep convolutional neural networks. Conference on Neural Information Processing Systems"},{"issue":"11","key":"9870_CR14","first-page":"5522","volume":"11","author":"G Lin","year":"2017","unstructured":"Lin G, Zhang Y, Zhang Q, Jia Y, Xu G, Wang J (2017) Smoke detection in video sequences based on dynamic texture using volume local binary patterns. KSII Trans Internet Inf Syst 11(11):5522\u20135536","journal-title":"KSII Trans Internet Inf Syst"},{"key":"9870_CR15","doi-asserted-by":"crossref","unstructured":"Lu X, et al. (2019) See more, know more: unsupervised video object segmentation with co-attention siamese networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","DOI":"10.1109\/CVPR.2019.00374"},{"key":"9870_CR16","doi-asserted-by":"crossref","unstructured":"Munsell Color System (2009) In: Manutchehr-Danai M. Dictionary of Gems and Gemology","DOI":"10.1007\/978-3-540-72816-0"},{"issue":"6","key":"9870_CR17","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"SQ Ren","year":"2015","unstructured":"Ren SQ, He KM, Ross G et al (2015) Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis & Machine Intelligence 39(6):1137\u20131149","journal-title":"IEEE Transactions on Pattern Analysis & Machine Intelligence"},{"key":"9870_CR18","unstructured":"Ryser P, Pfister G (1991) Optical fire and security technology: sensor principles and detection intelligence. International Conference on Solid-state Sensors & Actuators IEEE"},{"key":"9870_CR19","doi-asserted-by":"crossref","unstructured":"Tao CY, Zhang J, Wang P (2016) Smoke detection based on deep convolutional neural networks. International Conference on Industrial Informatics-computing Technology IEEE","DOI":"10.1109\/ICIICII.2016.0045"},{"issue":"5","key":"9870_CR20","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1016\/j.firesaf.2011.03.003","volume":"46","author":"TX Tung","year":"2011","unstructured":"Tung TX, Kim JM (2011) An effective four-stage smoke-detection algorithm using video images for early fire-alarm systems. Fire Saf J 46(5):276\u2013282","journal-title":"Fire Saf J"},{"issue":"3","key":"9870_CR21","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.firesaf.2012.07.005","volume":"57","author":"S Verstockt","year":"2013","unstructured":"Verstockt S, Van Hoecke S, Beji T et al (2013) A multi-modal video analysis approach for car park fire detection. Fire Saf J 57(3):44\u201357","journal-title":"Fire Saf J"},{"key":"9870_CR22","doi-asserted-by":"crossref","unstructured":"Wang W, Lu X, Shen J, et al. (2019) Zero-shot video object segmentation via attentive graph neural networks. IEEE International Conference on Computer Vision (ICCV)","DOI":"10.1109\/ICCV.2019.00933"},{"key":"9870_CR23","doi-asserted-by":"publisher","first-page":"18429","DOI":"10.1109\/ACCESS.2017.2747399","volume":"5","author":"ZJ Yin","year":"2017","unstructured":"Yin ZJ, Wan BY, Yuan FN et al (2017) A deep normalization and convolutional neural network for image smoke detection. IEEE Access 5:18429\u201318438","journal-title":"IEEE Access"},{"issue":"3","key":"9870_CR24","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.firesaf.2011.01.001","volume":"46","author":"FN Yuan","year":"2011","unstructured":"Yuan FN (2011) Video-based smoke detection with histogram sequence of LBP and LBPV pyramids. Fire Saf J 46(3):132\u2013139","journal-title":"Fire Saf J"},{"key":"9870_CR25","doi-asserted-by":"crossref","unstructured":"Zhang F, Qin W, Liu Y, et al. (2020) dual-channel convolution neural network for image smoke detection. Multimedia Tools and Applications","DOI":"10.1007\/s11042-019-08551-8"},{"issue":"7","key":"9870_CR26","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1016\/j.patrec.2005.11.005","volume":"27","author":"Z Zivkovic","year":"2006","unstructured":"Zivkovic Z, Heijden FVD (2006) Efficient adaptive density estimation per image pixel for the task of background subtraction. Pattern Recogn Lett 27(7):773\u2013780","journal-title":"Pattern Recogn Lett"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09870-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09870-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09870-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T17:26:32Z","timestamp":1638293192000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09870-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,6]]},"references-count":26,"journal-issue":{"issue":"28-29","published-print":{"date-parts":[[2021,11]]}},"alternative-id":["9870"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09870-x","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,6]]},"assertion":[{"value":"19 January 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}