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1. Kong, S.G., Jin, D., Li, S., Kim, H.. Fast fire flame detection in surveillance video using logistic regression and temporal smoothing. Fire safety journal, vol.79, 37-43.

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2. 이승희, 신범주, 송복득, 안선정, 김진동, 이학준. 영상 접합을 이용한 산불 감시 시스템. 한국콘텐츠학회논문지 = The Journal of the Korea Contents Association, vol.13, no.6, 40-47.

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3. Shin, Sung Gyun, Kim, Joo Yeon, Jang, Seungsoo, Lee, Min-Jae, Han, Sangsoo, Choi, Chan-Ho, Kim, Sungkyum, Cho, Woo-Sung, Lee, Janghee, Kim, Song Hyun. A Feasibility Study on Deep Learning-based Automatic Extinguishing Bullet Dropping Point Recommendation for Wildfire Suppression. 韓國情報技術學會論文誌 = Journal of Korean institute of information technology, vol.19, no.3, 15-23.

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4. 김별, 황광일. 딥러닝 기반의 연기 확산거리 예측을 위한 알고리즘 개발 기초연구. 海洋環境安全學會誌 = Journal of the Korean society of marine environment & safety, vol.27, no.1, 22-28.

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5. Chung, Dong Ki, Lee, Myung Hwa, Kim, Hwi Young, Park, Jeong Yong, Lee, Im Pyeong. Development of Forest Fire Monitoring System Using a Long-Term Endurance Solar Powered Drone and Deep Learning. 대한공간정보학회지 = Journal of Korean Society for Geospatial Information Science, vol.28, no.2, 29-38.

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6. Lee, Pyeong-Hwa, Song, Ju-Whan. Forest Fire Object Detection Using Deep Learning-Based Algorithm. 디지털콘텐츠학회 논문지 = Journal of Digital Contents Society, vol.23, no.9, 1869-1877.

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7. Kim, Yun-ji, Cho, Hyun-chong. Detecting Location of Fire in Video Stream Environment using Deep Learning. 전기학회논문지 = The Transactions of the Korean Institute of Electrical Engineers, vol.69, no.3, 474-479.

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8. Saponara, Sergio, Elhanashi, Abdussalam, Gagliardi, Alessio. Real-time video fire/smoke detection based on CNN in antifire surveillance systems. Journal of real-time image processing, vol.18, no.3, 889-900.

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9. T. H. Kim and J. J. Park, "Image Segmentation for Fire Prediction using Deep Learning", The Journal of The Institute of Internet, Broadcasting and Communication, Vol. 23, No. 1, pp. 65-70, Feb. 2023. https://doi.org/10.7236/JIIBC.2023.23.1.65. 

10. Zhang, Qi-xing, Lin, Gao-hua, Zhang, Yong-ming, Xu, Gao, Wang, Jin-jun. Wildland Forest Fire Smoke Detection Based on Faster R-CNN using Synthetic Smoke Images. Procedia engineering, vol.211, 441-446.

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11. Cao, Yichao, Yang, Feng, Tang, Qingfei, Lu, Xiaobo. An Attention Enhanced Bidirectional LSTM for Early Forest Fire Smoke Recognition. IEEE access : practical research, open solutions, vol.7, 154732-154742.

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12. Hossain, F.M. Anim, Zhang, Youmin M., Tonima, Masuda Akter. Forest fire flame and smoke detection from UAV-captured images using fire-specific color features and multi-color space local binary pattern. Journal of unmanned vehicle systems = Revue des systèmes de véhicules télécommandés, vol.8, no.4, 285-309.

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13. Jeong, Mira, Park, MinJi, Nam, Jaeyeal, Ko, Byoung Chul. Light-Weight Student LSTM for Real-Time Wildfire Smoke Detection. Sensors, vol.20, no.19, 5508-.

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14. Sousa, Maria João, Moutinho, Alexandra, Almeida, Miguel. Wildfire detection using transfer learning on augmented datasets. Expert systems with applications, vol.142, 112975-.

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15. 류진규, 곽동걸. 딥러닝 기반의 합성곱 신경망을 이용한 화염 및 연기 감지 알고리즘에 관한 연구. 한국방재학회논문집 = Journal of the Korean Society of Hazard Mitigation, vol.20, no.1, 223-232.

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16. J. Kim, T. Kwak, and Y. I. Kim, "A Study on Transferring Cloud Dataset for Smoke Extraction Based on Deep Learning", Korean Journal of Remote Sensing, Vol. 38, No. 5, pp. 695-706, Oct. 2022. http://doi.org/10.7780/kjrs.2022.38.5.2.4. 

17. M. J. Kim, K. R. Kim, and S. H. Baek, "Development of a disaster information delivery application using Cell Broadcast Service", The Journal of The Institute of Internet, Broadcasting and Communication, Vol. 21, No. 6, pp. 57-63, Dec. 2021. https://doi.org/10.7236/JIIBC.2021.21.6.57.