{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T07:31:34Z","timestamp":1771054294980,"version":"3.50.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T00:00:00Z","timestamp":1686873600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T00:00:00Z","timestamp":1686873600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62076199"],"award-info":[{"award-number":["62076199"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Key R\\&D project of Shaan'xi Province","award":["2021GY\u2010027"],"award-info":[{"award-number":["2021GY\u2010027"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Real-Time Image Proc"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s11554-023-01331-6","type":"journal-article","created":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T04:02:18Z","timestamp":1686888138000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["An efficient lightweight CNN model for real-time fire smoke detection"],"prefix":"10.1007","volume":"20","author":[{"given":"Bangyong","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siyuan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,16]]},"reference":[{"issue":"2","key":"1331_CR1","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1080\/13669870802648528","volume":"12","author":"B Ashe","year":"2009","unstructured":"Ashe, B., McAneney, K.J., Pitman, A.: Total Cost of Fire in Australia. J. Risk Res. 12(2), 121\u2013136 (2009)","journal-title":"J. Risk Res."},{"key":"1331_CR2","doi-asserted-by":"crossref","unstructured":"Healey, G., Slater, D., Lin, T., Drda, B., Goedeke, A.D.: A System for Real-time Fire Detection. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 605-606 (1993)","DOI":"10.1109\/CVPR.1993.341064"},{"key":"1331_CR3","doi-asserted-by":"crossref","unstructured":"Celik, T., Ozkaramanli, H., Demirel, H.: Fire Pixel Classification Using Fuzzy Logic and Statistical Color Model. In: Proceedings of IEEE International Conference on Acoustics,Speech and Signal Processing, pp. 1205-1208(2007)","DOI":"10.1109\/ICASSP.2007.366130"},{"key":"1331_CR4","doi-asserted-by":"crossref","unstructured":"Toreyin, B.U., Dedeoglu, Y., Cetin, A.E.: Flame Detection in Video Using Hidden Markov Models. In: Proceedings of IEEE International Conference on Image Processing, pp. 1230-1233 (2005)","DOI":"10.1109\/ICIP.2005.1530284"},{"issue":"8","key":"1331_CR5","doi-asserted-by":"publisher","first-page":"2312","DOI":"10.1007\/s10489-020-01676-6","volume":"50","author":"Y Gao","year":"2020","unstructured":"Gao, Y., Xie, L., Zhang, Z., Fan, Q.: Twin Support Vector Machine Based on Improved Artificial Fish Swarm Algorithm with Application to Flame Recognition. Appl. Intell. 50(8), 2312\u20132327 (2020)","journal-title":"Appl. Intell."},{"key":"1331_CR6","doi-asserted-by":"crossref","unstructured":"Wu, S., Zhang, L.: Using Popular Object Detection Methods for Real Time Forest Fire Detection. In: Proceedings of International Symposium on Computational Intelligence and Design, pp. 280-284 (2018)","DOI":"10.1109\/ISCID.2018.00070"},{"key":"1331_CR7","doi-asserted-by":"crossref","unstructured":"Bai, X., Wang, Z.: Research on Forest Fire Detection Technology Based on Deep Learning. In: Proceedings of International Conference on Computer Network, Electronic and Automation, pp. 85-90 (2021)","DOI":"10.1109\/ICCNEA53019.2021.00029"},{"key":"1331_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, Q.-x., Lin, G.-h., Zhang, Y.-m., Xu, G., Wang, J.-j.: Wildland Forest Fire Smoke Detection Based on Faster R-CNN Using Synthetic Smoke Images. Procedia Engineering 211, 441-446 (2018)","DOI":"10.1016\/j.proeng.2017.12.034"},{"key":"1331_CR9","doi-asserted-by":"crossref","unstructured":"Dzigal, D., Akagic, A., Buza, E., Brdjanin, A., Dardagan, N.: Forest Fire Detection Based on Color Spaces Combination. In: Proceedings of International Conference on Electrical and Electronics Engineering, pp. 595-599 (2019)","DOI":"10.23919\/ELECO47770.2019.8990608"},{"key":"1331_CR10","doi-asserted-by":"crossref","unstructured":"Pritam, D., Dewan, J.H.: Detection of Fire Using Image Processing Techniques with Luv Color Space. In: Proceedings of International Conference for Convergence in Technology, pp. 1158-1162 (2017)","DOI":"10.1109\/I2CT.2017.8226309"},{"issue":"2","key":"1331_CR11","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1109\/TCSVT.2014.2339592","volume":"25","author":"K Dimitropoulos","year":"2014","unstructured":"Dimitropoulos, K., Barmpoutis, P., Grammalidis, N.: Spatio-Temporal Flame Modeling and Dynamic Texture Analysis for Automatic Video-Based Fire Detection. IEEE Trans. Circuits Syst. Video Technol. 25(2), 339\u2013351 (2014)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"1331_CR12","doi-asserted-by":"crossref","unstructured":"Surit, S., Chatwiriya, W.: Forest Fire Smoke Detection in Video Based on Digital Image Processing Approach with Static and Dynamic Characteristic Analysis. In: Proceedings of International Conference on Computers, Networks, Systems and Industrial Engineering, pp. 35-39 (2011)","DOI":"10.1109\/CNSI.2011.47"},{"issue":"5","key":"1331_CR13","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1016\/j.buildenv.2009.10.017","volume":"45","author":"J Chen","year":"2010","unstructured":"Chen, J., He, Y., Wang, J.: Multi-Feature Fusion Based Fast Video Flame Detection. Build. Environ. 45(5), 1113\u20131122 (2010)","journal-title":"Build. Environ."},{"issue":"8","key":"1331_CR14","doi-asserted-by":"publisher","first-page":"1419","DOI":"10.1007\/s11760-017-1102-y","volume":"11","author":"X-F Han","year":"2017","unstructured":"Han, X.-F., Jin, J.S., Wang, M.-J., Jiang, W., Gao, L., Xiao, L.-P.: Video Fire Detection Based on Gaussian Mixture Model and MultiColor Features. SIViP 11(8), 1419\u20131425 (2017)","journal-title":"SIViP"},{"issue":"01","key":"1331_CR15","first-page":"171","volume":"34","author":"H Wei","year":"2020","unstructured":"Wei, H., Wang, S., Xu, Y., Zhao, J., Xiao, M.: Forest Fire Image Recognition Algorithm of Sample Entropy Fusion and Clustering. J. Electron. Measure. Instrum. 34(01), 171\u2013177 (2020)","journal-title":"J. Electron. Measure. Instrum."},{"key":"1331_CR16","doi-asserted-by":"crossref","unstructured":"Frizzi, S., Kaabi, R., Bouchouicha, M., Ginoux, J.-M., Moreau, E., Fnaiech, F.: Convolutional Neural Network for Video Fire and Smoke Detection. In: Proceedings of Annual Conference of the IEEE Industrial Electronics Society, pp. 877-882 (2016)","DOI":"10.1109\/IECON.2016.7793196"},{"key":"1331_CR17","doi-asserted-by":"crossref","unstructured":"Son, G., Park, J.-S., Yoon, B.-W., Song, J.-G.: Video Based Smoke and Flame Detection Using Convolutional Neural Network. In: Proceedings of International Conference on Signal-Image Technology & Internet-Based Systems, pp. 365-368 (2018)","DOI":"10.1109\/SITIS.2018.00063"},{"issue":"7","key":"1331_CR18","doi-asserted-by":"publisher","first-page":"1419","DOI":"10.1109\/TSMC.2018.2830099","volume":"49","author":"K Muhammad","year":"2018","unstructured":"Muhammad, K., Ahmad, J., Lv, Z., Bellavista, P., Yang, P., Baik, S.W.: Efficient Deep CNN-Based Fire Detection and Localization in Video Surveillance Applications. IEEE Transactions on Systems, Man, and Cybernetics: Systems 49(7), 1419\u20131434 (2018)","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"key":"1331_CR19","doi-asserted-by":"crossref","unstructured":"Dua, M., Kumar, M., Charan, G.S., Ravi, P.S.: An Improved Approach for Fire Detection Using Deep Learning Models. In: Proceedings of International Conference on Industry 4.0 Technology, pp. 171-175 (2020)","DOI":"10.1109\/I4Tech48345.2020.9102697"},{"key":"1331_CR20","doi-asserted-by":"crossref","unstructured":"Huttner, V., Steffens, C.R., da Costa Botelho, S.S.: First Response Fire Combat: Deep Leaning Based Visible Fire Detection. In: 2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR), pp. 1-6 (2017)","DOI":"10.1109\/SBR-LARS-R.2017.8215312"},{"key":"1331_CR21","doi-asserted-by":"publisher","first-page":"58923","DOI":"10.1109\/ACCESS.2020.2982994","volume":"8","author":"C Chaoxia","year":"2020","unstructured":"Chaoxia, C., Shang, W., Zhang, F.: Information-Guided Flame Detection Based on Faster R-CNN. IEEE Access 8, 58923\u201358932 (2020)","journal-title":"IEEE Access"},{"key":"1331_CR22","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.psep.2019.05.016","volume":"127","author":"H Wu","year":"2019","unstructured":"Wu, H., Wu, D., Zhao, J.: An Intelligent Fire Detection Approach Through Cameras Based on Computer Vision Methods. Process Saf. Environ. Prot. 127, 245\u2013256 (2019)","journal-title":"Process Saf. Environ. Prot."},{"key":"1331_CR23","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: Cbam: Convolutional Block Attention Module. In: Proceedings of the European Conference on Computer Vision, pp. 3-19 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"1331_CR24","doi-asserted-by":"crossref","unstructured":"Han, K., Wang, Y., Tian, Q., Guo, J., Xu, C., Xu, C.: Ghostnet: More Features from Cheap Operations. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1580-1589 (2020)","DOI":"10.1109\/CVPR42600.2020.00165"},{"key":"1331_CR25","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and Excitation Networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132-7141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1331_CR26","doi-asserted-by":"crossref","unstructured":"Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.: Path Aggregation Network for Instance Segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8759-8768 (2018)","DOI":"10.1109\/CVPR.2018.00913"},{"key":"1331_CR27","unstructured":"Wu, S., Zhang, X., Liu, R., Li, B.: A Dataset for Fire and Smoke Object Detection. Multimedia Tools and Applications, 1-20 (2022)"},{"issue":"2","key":"1331_CR28","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.firesaf.2008.05.005","volume":"44","author":"T Celik","year":"2009","unstructured":"Celik, T., Demirel, H.: Fire Detection in Video Sequences Using a Generic Color Model. Fire Saf. J. 44(2), 147\u2013158 (2009)","journal-title":"Fire Saf. J."},{"key":"1331_CR29","doi-asserted-by":"crossref","unstructured":"Zhang, D., Han, S., Zhao, J., Zhang, Z., Qu, C., Ke, Y., Chen, X.: Image Based Forest Fire Detection Using Dynamic Characteristics with Artificial Neural Networks. In: Proceedings of International Joint Conference on Artificial Intelligence, pp. 290-293 (2009)","DOI":"10.1109\/JCAI.2009.79"},{"key":"1331_CR30","doi-asserted-by":"crossref","unstructured":"Wang, S., Chen, T., Lv, X., Zhao, J., Zou, X., Zhao, X., Xiao, M., Wei, H.: Forest Fire Detection Based on Lightweight Yolo. In: Proceedings of Chinese Control and Decision Conference, pp. 1560-1565 (2021)","DOI":"10.1109\/CCDC52312.2021.9601362"},{"key":"1331_CR31","unstructured":"Li, W., Yu, Z.: A Lightweight Convolutional Neural Network Flame Detection Algorithm. In: Proceedings of International Conference on Electronics Information and Emergency Communication, pp. 83-86 (2021)"},{"issue":"9","key":"1331_CR32","doi-asserted-by":"publisher","first-page":"4930","DOI":"10.3390\/su14094930","volume":"14","author":"L Zhao","year":"2022","unstructured":"Zhao, L., Zhi, L., Zhao, C., Zheng, W.: Fire-Yolo: A Small Target Object Detection Method for Fire Inspection. Sustainability 14(9), 4930 (2022)","journal-title":"Sustainability"},{"key":"1331_CR33","doi-asserted-by":"publisher","first-page":"8467","DOI":"10.1109\/TIP.2020.3016431","volume":"29","author":"S Li","year":"2020","unstructured":"Li, S., Yan, Q., Liu, P.: An Efficient Fire Detection Method Based on Multiscale Feature Extraction, Implicit Deep Supervision and Channel Attention Mechanism. IEEE Trans. Image Process. 29, 8467\u20138475 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"1331_CR34","doi-asserted-by":"crossref","unstructured":"Tan, M., Pang, R., Le, Q.V.: Efficientdet: Scalable and Efficient Object Detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 10781-10790 (2020)","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"1331_CR35","unstructured":"Ge, Z., Liu, S., Wang, F., Li, Z., Sun, J.: Yolox: Exceeding Yolo Series in 2021. arXiv preprint arXiv:2107.08430 (2021)"},{"key":"1331_CR36","unstructured":"Yu, G., Chang, Q., Lv, W., Xu, C., Cui, C., Ji, W., Dang, Q., Deng, K., Wang, G., Du, Y., et al.: PP-Picodet: A Better Real-Time Object Detector on Mobile Devices. arXiv preprint arXiv:2111.00902 (2021)"},{"issue":"6","key":"1331_CR37","doi-asserted-by":"publisher","first-page":"2319","DOI":"10.1007\/s11554-021-01124-9","volume":"18","author":"S Wang","year":"2021","unstructured":"Wang, S., Zhao, J., Ta, N., Zhao, X., Xiao, M., Wei, H.: A Real-time Deep Learning Forest Fire Monitoring Algorithm Based on an Improved Pruned+ KD Model. J. Real-Time Image Proc. 18(6), 2319\u20132329 (2021)","journal-title":"J. Real-Time Image Proc."},{"key":"1331_CR38","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhang, W., Liu, Y., Jin, Y.: A Visualized Fire Detection Method Based on Convolutional Neural Network Beyond Anchor. Applied Intelligence, 1-16 (2022)","DOI":"10.1007\/s10489-022-03243-7"},{"key":"1331_CR39","doi-asserted-by":"crossref","unstructured":"Hongyu, H., Ping, K., Li, F., Huaxin, S.: An Improved Multi-scale Fire Detection Method Based on Convolutional Neural Network. In: Proceedings of International Computer Conference on Wavelet Active Media Technology and Information Processing, pp. 109-112 (2020)","DOI":"10.1109\/ICCWAMTIP51612.2020.9317360"},{"key":"1331_CR40","unstructured":"Bochkovskiy, A., Wang, C.-Y., Liao, H.- Y.M.: Yolov4: Optimal Speed and Accuracy of Object Detection. arXiv preprint arXiv:2004.10934 (2020)"}],"container-title":["Journal of Real-Time Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-023-01331-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11554-023-01331-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-023-01331-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T11:06:16Z","timestamp":1729595176000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11554-023-01331-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,16]]},"references-count":40,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["1331"],"URL":"https:\/\/doi.org\/10.1007\/s11554-023-01331-6","relation":{},"ISSN":["1861-8200","1861-8219"],"issn-type":[{"value":"1861-8200","type":"print"},{"value":"1861-8219","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,16]]},"assertion":[{"value":"7 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 June 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 June 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors certify that they have no affiliations with or involvement in any organization entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"74"}}