{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T23:06:41Z","timestamp":1762643201562,"version":"build-2065373602"},"publisher-location":"Singapore","reference-count":30,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819543977"},{"type":"electronic","value":"9789819543984"}],"license":[{"start":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T00:00:00Z","timestamp":1762646400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T00:00:00Z","timestamp":1762646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-4398-4_21","type":"book-chapter","created":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T16:37:05Z","timestamp":1762619825000},"page":"294-308","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bringing CLIP to\u00a0the\u00a0Edge: A Lightweight Fire Detection System for\u00a0Real-Time Monitoring with\u00a0UAV"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9109-8167","authenticated-orcid":false,"given":"HyeYoung","family":"Lee","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6551-8109","authenticated-orcid":false,"given":"Muhammad","family":"Nadeem","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,9]]},"reference":[{"issue":"19","key":"21_CR1","doi-asserted-by":"publisher","first-page":"6519","DOI":"10.3390\/s21196519","volume":"21","author":"A Abdusalomov","year":"2021","unstructured":"Abdusalomov, A., Baratov, N., Kutlimuratov, A., Whangbo, T.K.: An improvement of the fire detection and classification method using yolov3 for surveillance systems. Sensors 21(19), 6519 (2021)","journal-title":"Sensors"},{"key":"21_CR2","doi-asserted-by":"crossref","unstructured":"Akhloufi, M.A., Tokime, R.B., Elassady, H.: Wildland fires detection and segmentation using deep learning. In: Pattern Recognition and Tracking XXIX, vol. 10649, pp. 86\u201397. SPIE (2018)","DOI":"10.1117\/12.2304936"},{"key":"21_CR3","unstructured":"Associated Press: California governor asks congress for nearly \\$40 billion For Los Angeles wildfire relief (2025). https:\/\/apnews.com\/article\/71ec591a60c05d45432382095dbfd147. Accessed 25 Feb 2025"},{"key":"21_CR4","unstructured":"Avgerinakis, K., Briassouli, A., Kompatsiaris, I.: Smoke detection using temporal HOGHOF descriptors and energy colour statistics from video. In: International Workshop on Multi-sensor Systems and Networks for Fire Detection and Management (2012)"},{"key":"21_CR5","doi-asserted-by":"crossref","unstructured":"Barmpoutis, P., Dimitropoulos, K., Kaza, K., Grammalidis, N.: Fire detection from images using faster R-CNN and multidimensional texture analysis. ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8301\u20138305 (2019)","DOI":"10.1109\/ICASSP.2019.8682647"},{"issue":"22","key":"21_CR6","doi-asserted-by":"publisher","first-page":"6442","DOI":"10.3390\/s20226442","volume":"20","author":"P Barmpoutis","year":"2020","unstructured":"Barmpoutis, P., Papaioannou, P., Dimitropoulos, K., Grammalidis, N.: A review on early forest fire detection systems using optical remote sensing. Sensors 20(22), 6442 (2020)","journal-title":"Sensors"},{"issue":"1","key":"21_CR7","doi-asserted-by":"publisher","first-page":"98","DOI":"10.3390\/sym13010098","volume":"13","author":"VS Bochkov","year":"2021","unstructured":"Bochkov, V.S., Kataeva, L.Y.: WUUNet: advanced fully convolutional neural network for multiclass fire segmentation. Symmetry 13(1), 98 (2021)","journal-title":"Symmetry"},{"issue":"6","key":"21_CR8","doi-asserted-by":"publisher","first-page":"1827","DOI":"10.1016\/j.dsp.2013.07.003","volume":"23","author":"AE \u00c7etin","year":"2013","unstructured":"\u00c7etin, A.E., et al.: Video fire detection-review. Digit. Signal Process. 23(6), 1827\u20131843 (2013)","journal-title":"Digit. Signal Process."},{"issue":"13","key":"21_CR9","doi-asserted-by":"publisher","first-page":"5040","DOI":"10.1080\/01431161.2022.2119110","volume":"43","author":"C Ding","year":"2022","unstructured":"Ding, C., Zhang, X., Chen, J., Ma, S., Lu, Y., Han, W.: Wildfire detection through deep learning based on Himawari-8 satellites platform. Int. J. Remote Sens. 43(13), 5040\u20135058 (2022)","journal-title":"Int. J. Remote Sens."},{"issue":"4","key":"21_CR10","doi-asserted-by":"publisher","first-page":"624","DOI":"10.4314\/fuoyejet.v9i4.9","volume":"9","author":"A Hassan","year":"2024","unstructured":"Hassan, A., Audu, A.I.: A lightweight CNN model for vision based fire detection on embedded systems. FUOYE J. Eng. Technol. 9(4), 624\u2013628 (2024)","journal-title":"FUOYE J. Eng. Technol."},{"issue":"1","key":"21_CR11","doi-asserted-by":"publisher","first-page":"5979","DOI":"10.1038\/s41598-022-09954-8","volume":"12","author":"SA Hicks","year":"2022","unstructured":"Hicks, S.A., et al.: On evaluation metrics for medical applications of artificial intelligence. Sci. Rep. 12(1), 5979 (2022)","journal-title":"Sci. Rep."},{"key":"21_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.104737","volume":"110","author":"L Huang","year":"2022","unstructured":"Huang, L., Liu, G., Wang, Y., Yuan, H., Chen, T.: Fire detection in video surveillances using convolutional neural networks and wavelet transform. Eng. Appl. Artif. Intell. 110, 104737 (2022)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"21_CR13","doi-asserted-by":"crossref","unstructured":"Khryashchev, V., Larionov, R.: Wildfire segmentation on satellite images using deep learning. In: 2020 Moscow Workshop on Electronic and Networking Technologies (MWENT), pp.\u00a01\u20135 (2020)","DOI":"10.1109\/MWENT47943.2020.9067475"},{"key":"21_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/978-3-319-46448-0_2","volume-title":"Computer Vision \u2013 ECCV 2016","author":"W Liu","year":"2016","unstructured":"Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21\u201337. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2"},{"key":"21_CR15","doi-asserted-by":"crossref","unstructured":"Mannor, S., Peleg, D., Rubinstein, R.: The cross entropy method for classification. In: Proceedings of the 22nd International Conference on Machine Learning, vol. 22, pp. 561\u2013568 (2005)","DOI":"10.1145\/1102351.1102422"},{"issue":"7","key":"21_CR16","first-page":"3523","volume":"44","author":"S Minaee","year":"2021","unstructured":"Minaee, S., Boykov, Y., Porikli, F., Plaza, A., Kehtarnavaz, N., Terzopoulos, D.: Image segmentation using deep learning: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(7), 3523\u20133542 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"7","key":"21_CR17","doi-asserted-by":"publisher","first-page":"2786","DOI":"10.1109\/TIP.2013.2258353","volume":"22","author":"M Mueller","year":"2013","unstructured":"Mueller, M., Karasev, P., Kolesov, I., Tannenbaum, A.: Optical flow estimation for flame detection in videos. IEEE Trans. Image Process. 22(7), 2786\u20132797 (2013)","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"21_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 Trans. Syst. Man Cybernet. Syst. 49(7), 1419\u20131434 (2018)","journal-title":"IEEE Trans. Syst. Man Cybernet. Syst."},{"key":"21_CR19","doi-asserted-by":"crossref","unstructured":"Nguyen, A., Nguyen, H., Tran, V., Pham, H.X., Pestana, J.: A visual real-time fire detection using single shot multibox detector for UAV-based fire surveillance. In: 2020 IEEE Eighth International Conference on Communications and Electronics (ICCE), pp. 338\u2013343 (2021)","DOI":"10.1109\/ICCE48956.2021.9352080"},{"key":"21_CR20","unstructured":"O\u2019shea, K., Nash, R.: An introduction to convolutional neural networks. arXiv preprint arXiv:1511.08458 (2015)"},{"key":"21_CR21","volume":"116","author":"S Qurratulain","year":"2023","unstructured":"Qurratulain, S., Zheng, Z., Xia, J., Ma, Y., Zhou, F.: Deep learning instance segmentation framework for burnt area instances characterization. Int. J. Appl. Earth Obs. Geoinf. 116, 103146 (2023)","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"21_CR22","unstructured":"Radford, A., Kim, J.W., et\u00a0al.: Learning transferable visual models from natural language supervision. In: Proceedings of the International Conference on Machine Learning (ICML), pp. 8748\u20138763 (2021)"},{"issue":"35","key":"21_CR23","doi-asserted-by":"publisher","first-page":"83427","DOI":"10.1007\/s11042-024-18685-z","volume":"83","author":"L Ramos","year":"2024","unstructured":"Ramos, L., Casas, E., Bendek, E., Romero, C., Rivas-Echeverr\u00eda, F.: Computer vision for wildfire detection: a critical brief review. Multimedia Tools Appl. 83(35), 83427\u201383470 (2024)","journal-title":"Multimedia Tools Appl."},{"key":"21_CR24","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"21_CR25","unstructured":"Statista: Number of forest fires in South Korea (2023). https:\/\/www.statista.com\/statistics\/1296399\/south-korea-forest-fire-outbreaks\/. Accessed 25 Feb 2025"},{"issue":"28","key":"21_CR26","doi-asserted-by":"publisher","first-page":"20939","DOI":"10.1007\/s00521-023-08809-1","volume":"35","author":"FM Talaat","year":"2023","unstructured":"Talaat, F.M., ZainEldin, H.: An improved fire detection approach based on YOLO-v8 for smart cities. Neural Comput. Appl. 35(28), 20939\u201320954 (2023)","journal-title":"Neural Comput. Appl."},{"issue":"6","key":"21_CR27","doi-asserted-by":"publisher","first-page":"067204","DOI":"10.1117\/1.2748752","volume":"46","author":"BU T\u00f6reyin","year":"2007","unstructured":"T\u00f6reyin, B.U., Cinbi\u015f, R.G., Dedeo\u011flu, Y., \u00c7etin, A.E.: Fire detection in infrared video using wavelet analysis. Opt. Eng. 46(6), 067204\u2013067204 (2007)","journal-title":"Opt. Eng."},{"key":"21_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.firesaf.2020.102977","volume":"113","author":"X Wang","year":"2020","unstructured":"Wang, X., et al.: Evaluation of gas and particle sensors for detecting spacecraft-relevant fire emissions. Fire Saf. J. 113, 102977 (2020)","journal-title":"Fire Saf. J."},{"key":"21_CR29","doi-asserted-by":"crossref","unstructured":"Xu, S.G., Kong, S., Asgharzadeh, Z.: Wildfire detection using streaming satellite imagery. In: Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2899\u20132902 (2021)","DOI":"10.1109\/IGARSS47720.2021.9554904"},{"key":"21_CR30","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1007\/s10694-012-0253-1","volume":"50","author":"Z Zhang","year":"2014","unstructured":"Zhang, Z., Shen, T., Zou, J.: An improved probabilistic approach for fire detection in videos. Fire Technol. 50, 745\u2013752 (2014)","journal-title":"Fire Technol."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-4398-4_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T23:02:05Z","timestamp":1762642925000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-4398-4_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,9]]},"ISBN":["9789819543977","9789819543984"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-4398-4_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,11,9]]},"assertion":[{"value":"9 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gold Coast, QLD","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"acpr2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.acpr2025.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}