{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T22:40:59Z","timestamp":1761864059485,"version":"3.37.3"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"45-46","license":[{"start":{"date-parts":[[2020,1,6]],"date-time":"2020-01-06T00:00:00Z","timestamp":1578268800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,6]],"date-time":"2020-01-06T00:00:00Z","timestamp":1578268800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Tianjin Educational Science and Research","award":["no.2017KJ087"],"award-info":[{"award-number":["no.2017KJ087"]}]},{"name":"Tianjin Science and Technology Major Projects and Engineering","award":["No.17ZXHLSY00040 and No.17ZXSCSY00090"],"award-info":[{"award-number":["No.17ZXHLSY00040 and No.17ZXSCSY00090"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1007\/s11042-019-08551-8","type":"journal-article","created":{"date-parts":[[2020,1,6]],"date-time":"2020-01-06T06:02:31Z","timestamp":1578290551000},"page":"34587-34603","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["A Dual-Channel convolution neural network for image smoke detection"],"prefix":"10.1007","volume":"79","author":[{"given":"Fang","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2105-0931","authenticated-orcid":false,"given":"Yanbei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhitao","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinxin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaihua","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,1,6]]},"reference":[{"key":"8551_CR1","unstructured":"Chen T, Kao C, Chang S (2003) An intelligent real-time fire-detection method based on video processing. IEEE International Carnahan Conference on Security Technology IEEE"},{"key":"8551_CR2","doi-asserted-by":"crossref","unstructured":"Chen T et al (2006) The smoke detection for early fire-alarming system based on video processing. International Conference on Intelligent Information Hiding & Multimedia Signal Processing IEEE","DOI":"10.1109\/IIH-MSP.2006.265033"},{"key":"8551_CR3","unstructured":"Ciresan DC et al (2011) Flexible, high performance convolutional neural networks for image classification. IJCAI 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, DBLP"},{"key":"8551_CR4","unstructured":"Dalal N, Triggs B (2015) \u201cHistograms of oriented gradients for human detection. In: Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., pp. 886\u2013893"},{"key":"8551_CR5","doi-asserted-by":"crossref","unstructured":"Du, et al (2013) \u201cUnsupervised transfer learning for target detection from hyperspectral images.\u201d Neurocomputing 120: 72\u201382","DOI":"10.1016\/j.neucom.2012.08.056"},{"key":"8551_CR6","doi-asserted-by":"crossref","unstructured":"Gamon MA, Aue A (2005) Automatic identification of sentiment vocabulary: exploiting low. Acl Workshop on Feature Engineering for Machine Learning in Natural Language Processing Association for Computational Linguistics","DOI":"10.3115\/1610230.1610241"},{"issue":"8","key":"8551_CR7","doi-asserted-by":"publisher","first-page":"1110","DOI":"10.1016\/j.firesaf.2009.08.003","volume":"44","author":"J Gubbi","year":"2009","unstructured":"Gubbi J, Marusic S, Palaniswami M (2009) Smoke detection in video using wavelets and support vector machines. Fire Saf J 44(8):1110\u20131115","journal-title":"Fire Saf J"},{"key":"8551_CR8","doi-asserted-by":"crossref","unstructured":"Gui L et al (2017) Negative transfer detection in transductive transfer learning. Int J Mach Learn Cybern","DOI":"10.1007\/s13042-016-0634-8"},{"issue":"5","key":"8551_CR9","doi-asserted-by":"publisher","first-page":"2853","DOI":"10.1109\/TIP.2012.2183141","volume":"21","author":"O Gunay","year":"2012","unstructured":"Gunay O, Toreyin BU, Kose K, Cetin AE (2012) Entropy-functional-based online adaptive decision fusion framework with application to wildfire detection in video. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society 21(5):2853\u20132865","journal-title":"IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society"},{"key":"8551_CR10","doi-asserted-by":"crossref","unstructured":"Inoue T et al (2017) Transfer learning from synthetic to real images using variational autoencoders for robotic applications","DOI":"10.1109\/ICIP.2018.8451064"},{"issue":"4","key":"8551_CR11","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/s00138-012-0481-x","volume":"24","author":"T Jakov\u010devi\u0107","year":"2013","unstructured":"Jakov\u010devi\u0107 T, Stipani\u010dev D, Krstini\u0107 D (2013) Visual spatial-context based wildfire smoke sensor. Mach Vis Appl 24(4):707\u2013719","journal-title":"Mach Vis Appl"},{"key":"8551_CR12","unstructured":"James N (2010) \u201cReal-time fire detection in low quality video,\u201d Dissertations & Theses - Gradworks"},{"issue":"2","key":"8551_CR13","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1364\/BOE.8.000579","volume":"8","author":"SPK Karri","year":"2017","unstructured":"Karri SPK, Chatterjee J (2017) Transfer learning based classification of optical coherence tomography images with diabetic macular edema and dry age-related macular degeneration. Biomedical Optics Express 8(2):579","journal-title":"Biomedical Optics Express"},{"issue":"10","key":"8551_CR14","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1016\/j.imavis.2013.08.001","volume":"31","author":"BC Ko","year":"2013","unstructured":"Ko BC, Park JO, Nam JY (2013) Spatiotemporal bag-of-features for early wildfire smoke detection. Image Vis Comput 31(10):786\u2013795","journal-title":"Image Vis Comput"},{"issue":"4","key":"8551_CR15","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF00344251","volume":"36","author":"F Kunihiko","year":"1980","unstructured":"Kunihiko F (1980) Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol Cybern 36(4):193\u2013202","journal-title":"Biol Cybern"},{"key":"8551_CR16","doi-asserted-by":"publisher","unstructured":"Liu YB et al (2019) A Dual Convolution Network Using Dark Channel Prior for Image Smoke Classification. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2019.2915599","DOI":"10.1109\/ACCESS.2019.2915599"},{"issue":"4","key":"8551_CR17","doi-asserted-by":"publisher","first-page":"2315","DOI":"10.1109\/JIOT.2017.2737479","volume":"5","author":"H Lu","year":"2018","unstructured":"Lu H et al (2018) Motor anomaly detection for unmanned aerial vehicles using reinforcement learning. IEEE Internet Things J 5(4):2315\u20132322","journal-title":"IEEE Internet Things J"},{"key":"8551_CR18","doi-asserted-by":"crossref","unstructured":"Lu H et al (2018) Low illumination underwater light field images reconstruction using deep convolutional neural networks. Futur Gener Comput Syst 82","DOI":"10.1016\/j.future.2018.01.001"},{"key":"8551_CR19","doi-asserted-by":"crossref","unstructured":"Morerio P et al (2013) Early fire and smoke detection based on colour features and motion analysis. 2012 19th IEEE International Conference on Image Processing IEEE","DOI":"10.1109\/ICIP.2012.6467041"},{"key":"8551_CR20","doi-asserted-by":"crossref","unstructured":"Park J, Ko B, Nam JY, Kwak S (2013) Wildfire smoke detection using spatiotemporal bag-of-features of smoke. In: Proc. IEEE Workshop Appl. Comput. Vis., Jan., pp. 200\u2013205","DOI":"10.1109\/WACV.2013.6475019"},{"issue":"4","key":"8551_CR21","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1007\/s00138-010-0272-1","volume":"22","author":"C Simone","year":"2011","unstructured":"Simone C, Piccinini P, Cucchiara R (2011) Vision based smoke detection system using image energy and color information. Mach Vis Appl 22(4):705\u2013719","journal-title":"Mach Vis Appl"},{"key":"8551_CR22","unstructured":"State Key Lab of Fire Science. At University of Science and Technology of China [DB\/OL]. http:\/\/staff.ustc.edu.cn\/~yfn\/vsd.html"},{"key":"8551_CR23","doi-asserted-by":"crossref","unstructured":"Tian H et al (2011) Smoke detection in videos using non-redundant local binary pattern-based features. IEEE 13th International Workshop on Multimedia Signal Processing IEEE, 2011","DOI":"10.1109\/MMSP.2011.6093844"},{"key":"8551_CR24","unstructured":"Tian H et al (2017) Detection and separation of smoke from single image frames. IEEE Trans Image Process 1-1"},{"key":"8551_CR25","unstructured":"T\u00f6reyin B et al (2005) Wavelet based real-time smoke detection in video. European Signal Processing Conference IEEE"},{"key":"8551_CR26","doi-asserted-by":"crossref","unstructured":"Wan X (2009) Co-training for cross-lingual sentiment classification. Joint Conference of the Meeting of the Acl & the International Joint Conference on Natural Language Processing of the Afnlp: Volume Association for Computational Linguistics","DOI":"10.3115\/1687878.1687913"},{"key":"8551_CR27","unstructured":"Wang F (2016) Research on simulation of the spatial and temporal distribution characteristics of graphite smoke particle size. Guidance & Fuze"},{"key":"8551_CR28","unstructured":"Wang Y et al (2012) \u201cReal-time smoke detection using texture and color features. Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012) IEEE"},{"key":"8551_CR29","doi-asserted-by":"publisher","first-page":"18429","DOI":"10.1109\/ACCESS.2017.2747399","volume":"5","author":"Z Yin","year":"2017","unstructured":"Yin Z et al (2017) A deep normalization and convolutional neural network for image smoke detection. IEEE Access 5:18429\u201318438","journal-title":"IEEE Access"},{"issue":"7","key":"8551_CR30","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1016\/j.patrec.2008.01.013","volume":"29","author":"F Yuan","year":"2008","unstructured":"Yuan F (2008) A fast accumulative motion orientation model based on integral image for video smoke detection. Pattern Recogn Lett 29(7):925\u2013932","journal-title":"Pattern Recogn Lett"},{"issue":"12","key":"8551_CR31","doi-asserted-by":"publisher","first-page":"4326","DOI":"10.1016\/j.patcog.2012.06.008","volume":"45","author":"F Yuan","year":"2012","unstructured":"Yuan F (2012) A double mapping framework for extraction of shape-invariant features based on multi-scale partitions with adaboost for video smoke detection. Pattern Recogn 45(12):4326\u20134336","journal-title":"Pattern Recogn"},{"key":"8551_CR32","doi-asserted-by":"crossref","unstructured":"Zhang Y et al (2018) PEA: parallel electrocardiogram-based authentication for smart healthcare systems. J Netw Comput Appl","DOI":"10.1016\/j.jnca.2018.05.007"},{"key":"8551_CR33","doi-asserted-by":"publisher","unstructured":"Zhang C et al (2018) Generalized Latent Multi-View Subspace Clustering. IEEE Trans Pattern Anal Mach Intell. https:\/\/doi.org\/10.1109\/TPAMI.2018.2877660","DOI":"10.1109\/TPAMI.2018.2877660"},{"key":"8551_CR34","doi-asserted-by":"crossref","unstructured":"Zhou X, Wan X, Xiao J (2013) Cross-language opinion target extraction in review texts. IEEE International Conference on Data Mining IEEE","DOI":"10.1109\/ICDM.2012.32"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-08551-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-019-08551-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-08551-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T00:45:06Z","timestamp":1609807506000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-019-08551-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,6]]},"references-count":34,"journal-issue":{"issue":"45-46","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["8551"],"URL":"https:\/\/doi.org\/10.1007\/s11042-019-08551-8","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2020,1,6]]},"assertion":[{"value":"25 April 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 August 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 November 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 January 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}