{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T01:21:58Z","timestamp":1783128118595,"version":"3.54.6"},"reference-count":51,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62471189"],"award-info":[{"award-number":["62471189"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["W2433165"],"award-info":[{"award-number":["W2433165"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008083","name":"Xihua University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008083","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.engappai.2026.114891","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T10:06:24Z","timestamp":1777370784000},"page":"114891","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P2","title":["Credible early fire detection via intelligent pan\u2013tilt-zoom camera"],"prefix":"10.1016","volume":"177","author":[{"given":"Tian","family":"Deng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengpai","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaole","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edmore","family":"Tarambiwa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbo","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7667-9780","authenticated-orcid":false,"given":"Ang","family":"Bian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Nienk\u00f6tter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.engappai.2026.114891_b1","first-page":"4759","article-title":"Drone-based public surveillance using 3D point clouds and neuro-fuzzy classifier","volume":"82","author":"Abbas","year":"2025","journal-title":"Comput. Mater. Contin."},{"key":"10.1016\/j.engappai.2026.114891_b2","series-title":"2022 IEEE International Conference on Image Processing","first-page":"966","article-title":"Slicing aided hyper inference and fine-tuning for small object detection","author":"Akyon","year":"2022"},{"key":"10.1016\/j.engappai.2026.114891_b3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s40860-025-00244-4","article-title":"A fire management intelligent system for the Brazilian cerrado biome based on a deep learning two phase detection method","volume":"11","author":"Borges","year":"2025","journal-title":"J. Reliab. Intell. Environ."},{"key":"10.1016\/j.engappai.2026.114891_b4","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1007\/s44267-024-00053-y","article-title":"Efficient forest fire detection based on improved YOLO model","volume":"2","author":"Cao","year":"2024","journal-title":"Vis. Intell."},{"key":"10.1016\/j.engappai.2026.114891_b5","doi-asserted-by":"crossref","first-page":"111079","DOI":"10.1109\/ACCESS.2023.3322143","article-title":"YOLO-SF: YOLO for fire segmentation detection","volume":"11","author":"Cao","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.114891_b6","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.firesaf.2007.01.006","article-title":"Fire detection using smoke and gas sensors","volume":"42","author":"Chen","year":"2007","journal-title":"Fire Saf. J."},{"issue":"10","key":"10.1016\/j.engappai.2026.114891_b7","doi-asserted-by":"crossref","first-page":"18855","DOI":"10.1109\/TITS.2022.3161977","article-title":"Disparity-based multiscale fusion network for transportation detection","volume":"23","author":"Chen","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.engappai.2026.114891_b8","doi-asserted-by":"crossref","DOI":"10.1007\/s11227-025-07997-y","article-title":"WA-YOLO: a forest fire smoke detection method based on wavelet convolution and SimAM","volume":"81","author":"Chen","year":"2025","journal-title":"J. Supercomput."},{"key":"10.1016\/j.engappai.2026.114891_b9","doi-asserted-by":"crossref","first-page":"15349","DOI":"10.1007\/s00521-022-07467-z","article-title":"An automatic fire detection system based on deep convolutional neural networks for low-power, resource-constrained devices","volume":"34","author":"de Venancio","year":"2022","journal-title":"Neural Comput. Appl."},{"issue":"2","key":"10.1016\/j.engappai.2026.114891_b10","doi-asserted-by":"crossref","first-page":"3278","DOI":"10.1109\/JSEN.2025.3639441","article-title":"YCNNet: Road target recognition method by fusion of LiDAR and thermal infrared camera","volume":"26","author":"Deng","year":"2026","journal-title":"IEEE Sensors J."},{"issue":"9","key":"10.1016\/j.engappai.2026.114891_b11","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1109\/TCSVT.2015.2392531","article-title":"Real-time fire detection for video-surveillance applications using a combination of experts based on color, shape, and motion","volume":"25","author":"Foggia","year":"2015","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.engappai.2026.114891_b12","series-title":"YOLOv8 release v8.1.0","author":"Gelnn","year":"2024"},{"key":"10.1016\/j.engappai.2026.114891_b13","series-title":"Fire-smoke-detect-yolov4","author":"Gengyanlei","year":"2020"},{"key":"10.1016\/j.engappai.2026.114891_b14","doi-asserted-by":"crossref","unstructured":"Hongyou, C., Jineng, O., Leping, B., Zonghuang, C., 2021. Hardware Design of Fire Monitor Pan Tilt Control System. In: 2021 IEEE 4th International Conference on Electronics Technology. ICET, pp. 951\u2013954.","DOI":"10.1109\/ICET51757.2021.9451062"},{"key":"10.1016\/j.engappai.2026.114891_b15","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J., 2021. Coordinate attention for efficient mobile network design. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 13713\u201313722.","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"10.1016\/j.engappai.2026.114891_b16","doi-asserted-by":"crossref","first-page":"1142","DOI":"10.4028\/www.scientific.net\/AMM.52-54.1142","article-title":"Design of a new fire detection and alarm system based on self-organizing wireless sensor network","volume":"52","author":"Hu","year":"2011","journal-title":"Appl. Mech. Mater."},{"key":"10.1016\/j.engappai.2026.114891_b17","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G., 2018. Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 7132\u20137141.","DOI":"10.1109\/CVPR.2018.00745"},{"issue":"4","key":"10.1016\/j.engappai.2026.114891_b18","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1109\/LGRS.2019.2930308","article-title":"Vehicle detection in remote sensing images leveraging on simultaneous super-resolution","volume":"17","author":"Ji","year":"2020","journal-title":"IEEE Geosci. Remote. Sens. Lett."},{"key":"10.1016\/j.engappai.2026.114891_b19","series-title":"YOLOv5 release v7.0","author":"Jocher","year":"2022"},{"key":"10.1016\/j.engappai.2026.114891_b20","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1007\/s11554-023-01309-4","article-title":"A real-time fire detection method from video for electric vehicle-charging stations based on improved YOLOX-tiny","volume":"20","author":"Ju","year":"2023","journal-title":"J. Real-Time Image Process."},{"issue":"9","key":"10.1016\/j.engappai.2026.114891_b21","doi-asserted-by":"crossref","DOI":"10.1007\/s11760-025-04281-7","article-title":"Enhanced YOLO-IASE for robust safety inspection in complex substation environments","volume":"19","author":"Junjie","year":"2025","journal-title":"Signal Image Video Process."},{"key":"10.1016\/j.engappai.2026.114891_b22","first-page":"1","article-title":"The development of UV\/IR combination flame detector","volume":"16","author":"Lee","year":"2001","journal-title":"J. KIIS"},{"key":"10.1016\/j.engappai.2026.114891_b23","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.inffus.2022.10.007","article-title":"Image super-resolution: A comprehensive review, recent trends, challenges and applications","volume":"91","author":"Lepcha","year":"2023","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.engappai.2026.114891_b24","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/TCSVT.2018.2889193","article-title":"3D parallel fully convolutional networks for real-time video wildfire smoke detection","volume":"30","author":"Li","year":"2018","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.engappai.2026.114891_b25","series-title":"Rt-detrv2: Improved baseline with bag-of-freebies for real-time detection transformer","author":"Lv","year":"2024"},{"key":"10.1016\/j.engappai.2026.114891_b26","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.firesaf.2006.02.001","article-title":"An image processing technique for fire detection in video images","volume":"41","author":"Marbach","year":"2006","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.engappai.2026.114891_b27","doi-asserted-by":"crossref","first-page":"2786","DOI":"10.1109\/TIP.2013.2258353","article-title":"Optical flow estimation for flame detection in videos","volume":"22","author":"Mueller","year":"2013","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.engappai.2026.114891_b28","doi-asserted-by":"crossref","unstructured":"Ouyang, D., He, S., Zhang, G., Luo, M., Guo, H., Zhan, J., Huang, Z., 2023. Efficient multi-scale attention module with cross-spatial learning. In: ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP, pp. 1\u20135.","DOI":"10.1109\/ICASSP49357.2023.10096516"},{"key":"10.1016\/j.engappai.2026.114891_b29","doi-asserted-by":"crossref","unstructured":"Pan, W., Xu, B., Wang, X., Lv, C., Wang, S., Duan, Z., 26-29. YOLO-FireAD: Efficient Fire Detection via Attention-Guided Inverted Residual Learning and Dual-Pooling Feature Preservation. In: Proceedings of the 21st International Conference on Intelligent Computing. ICIC 2025, Ningbo, China, pp. 438\u2013452, Poster Volume I.","DOI":"10.65286\/icic.v21i1.31472"},{"key":"10.1016\/j.engappai.2026.114891_b30","doi-asserted-by":"crossref","unstructured":"Selvaragju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D., 2017. Grad-cam: Visual explanations from deep networks via gradient-based locations. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 618\u2013626.","DOI":"10.1109\/ICCV.2017.74"},{"key":"10.1016\/j.engappai.2026.114891_b31","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Bochkovskiy, A., Liao, H.Y.M., 2023. YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 7464\u20137475.","DOI":"10.1109\/CVPR52729.2023.00721"},{"key":"10.1016\/j.engappai.2026.114891_b32","doi-asserted-by":"crossref","first-page":"107984","DOI":"10.52202\/079017-3429","article-title":"Yolov10: Real-time end-to-end object detection","volume":"37","author":"Wang","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114891_b33","series-title":"Designing network design strategies through gradient path analysis","author":"Wang","year":"2022"},{"key":"10.1016\/j.engappai.2026.114891_b34","doi-asserted-by":"crossref","unstructured":"Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., Hu, Q., 2020. ECA-Net: Efficient channel attention for deep convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 11534\u201311542.","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"10.1016\/j.engappai.2026.114891_b35","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Yeh, I.H., Mark Liao, H.Y., 2024. Yolov9: Learning what you want to learn using programmable gradient information. In: European Conference on Computer Vision. pp. 1\u201321.","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"10.1016\/j.engappai.2026.114891_b36","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., Kweon, I.S., 2018. Cbam: Convolutional block attention module. In: Proceedings of the European Conference on Computer Vision. pp. 3\u201319.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"10.1016\/j.engappai.2026.114891_b37","doi-asserted-by":"crossref","first-page":"6707","DOI":"10.1007\/s11042-022-13580-x","article-title":"A dataset for fire and smoke object detection","volume":"82","author":"Wu","year":"2023","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.engappai.2026.114891_b38","doi-asserted-by":"crossref","first-page":"1812","DOI":"10.3390\/f14091812","article-title":"Fl-yolov7: A lightweight small object detection algorithm in forest fire detection","volume":"14","author":"Xiao","year":"2023","journal-title":"Forests"},{"key":"10.1016\/j.engappai.2026.114891_b39","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2024.114970","article-title":"ESMNet: An enhanced YOLOv7-based approach to detect surface defects in precision metal workpieces","volume":"235","author":"Xu","year":"2024","journal-title":"Measurement"},{"key":"10.1016\/j.engappai.2026.114891_b40","series-title":"ELA: Efficient local attention for deep convolutional neural networks","author":"Xu","year":"2024"},{"key":"10.1016\/j.engappai.2026.114891_b41","doi-asserted-by":"crossref","first-page":"1332","DOI":"10.3390\/f13081332","article-title":"A small target forest fire detection model based on YOLOv5 improvement","volume":"13","author":"Xue","year":"2022","journal-title":"Forests"},{"key":"10.1016\/j.engappai.2026.114891_b42","unstructured":"Yu, L., Wang, N., Meng, X., 2005. Real-time forest fire detection with wireless sensor networks. In: Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing. pp. 1214\u20131217."},{"key":"10.1016\/j.engappai.2026.114891_b43","doi-asserted-by":"crossref","unstructured":"Zhang, J., Li, W., Yin, Z., Liu, S., Guo, X., 2009. Forest fire detection system based on wireless sensor network. In: 2009 4th IEEE Conference on Industrial Electronics and Applications. pp. 520\u2013523.","DOI":"10.1109\/ICIEA.2009.5138260"},{"key":"10.1016\/j.engappai.2026.114891_b44","doi-asserted-by":"crossref","unstructured":"Zhang, C., Rameau, F., Kim, J., Argaw, D.M., Bazin, J.C., Kweon, I.S., 2020. Deepptz: Deep self-calibration for ptz cameras. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision. pp. 1041\u20131049.","DOI":"10.1109\/WACV45572.2020.9093629"},{"key":"10.1016\/j.engappai.2026.114891_b45","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Lv, W., Xu, S., Wei, J., Wang, G., Dang, Q., Liu, Y., Chen, J., 2024. DETRs Beat YOLOs on Real-time Object Detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 16965\u201316974.","DOI":"10.1109\/CVPR52733.2024.01605"},{"key":"10.1016\/j.engappai.2026.114891_b46","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1186\/s42408-023-00189-0","article-title":"Real-time fire detection algorithms running on small embedded devices based on MobilenetV3 and YOLOv4","volume":"19","author":"Zheng","year":"2023","journal-title":"Fire Ecol."},{"key":"10.1016\/j.engappai.2026.114891_b47","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2025.103516","article-title":"YOLO-MP: A lightweight forest fire detection model","volume":"92","author":"Zhu","year":"2025","journal-title":"Ecol. Inform."},{"issue":"29","key":"10.1016\/j.engappai.2026.114891_b48","doi-asserted-by":"crossref","first-page":"5672","DOI":"10.1111\/mice.70118","article-title":"A crack detection and quantification framework for high-resolution images using Mamba and unmanned devices","volume":"40","author":"Zhu","year":"2025","journal-title":"Comput.-Aided Civ. Infrastruct. Eng."},{"key":"10.1016\/j.engappai.2026.114891_b49","series-title":"Deformable detr: Deformable transformers for end-to-end object detection","author":"Zhu","year":"2020"},{"key":"10.1016\/j.engappai.2026.114891_b50","doi-asserted-by":"crossref","first-page":"6552","DOI":"10.3390\/s23146552","article-title":"Fire detection in ship engine rooms based on deep learning","volume":"23","author":"Zhu","year":"2023","journal-title":"Sensors"},{"issue":"3","key":"10.1016\/j.engappai.2026.114891_b51","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/JPROC.2023.3238524","article-title":"Object detection in 20 years: A survey","volume":"111","author":"Zou","year":"2023","journal-title":"Proc. IEEE"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626011735?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626011735?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T00:57:47Z","timestamp":1783126667000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626011735"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":51,"alternative-id":["S0952197626011735"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114891","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Credible early fire detection via intelligent pan\u2013tilt-zoom camera","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114891","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114891"}}