Laser & Optoelectronics Progress, Volume. 62, Issue 14, 1437003(2025)

LEM-YOLO-Based Lightweight Multi-Scale Detection of Forest Fire Smoke in UAV Imagery

Ruijie Kuang1, Xiang Li2、*, Yu Liu1, Bingying Hu2, and Xianshun Wang2
Author Affiliations
  • 1College of Information Engineering, East China University of Technology, Nanchang 330013, Jiangxi , China
  • 2College of Software, East China University of Technology, Fuzhou 344199, Jiangxi , China
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    References(31)

    [1] Liu H L, Fang Q, Jiang Y et al. A lightweight forest fire detection algorithm based on YOLOv5s[J]. China Safety Science Journal, 35, 75-83(2025).

    [4] Zhang X B, Qian K, Jing K H et al. Fire detection based on convolutional neural networks with channel attention[C], 3080-3085(2020).

    [8] Cao L Y, Yang Y Z, Li S L et al. Research on forest fire monitoring technology for complex scenarios[J]. Radio Communications Technology, 50, 779-788(2024).

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    Ruijie Kuang, Xiang Li, Yu Liu, Bingying Hu, Xianshun Wang. LEM-YOLO-Based Lightweight Multi-Scale Detection of Forest Fire Smoke in UAV Imagery[J]. Laser & Optoelectronics Progress, 2025, 62(14): 1437003

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    Paper Information

    Category: Digital Image Processing

    Received: Apr. 10, 2025

    Accepted: May. 7, 2025

    Published Online: Jul. 15, 2025

    The Author Email: Xiang Li (tom_lx@126.com)

    DOI:10.3788/LOP250979

    CSTR:32186.14.LOP250979

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