An early UAV coal fire infrared image target detection and recognition method in open-pit coal mines

doi:10.13474/j.cnki.11-2246.2025.1011

Abstract

Abstract: In view of the current difficulties in early detection of coal fires in open-pit coal mines and the late discovery time, this paper proposes an improved UAV infrared image target detection and recognition method for early coal seam spontaneous combustion in open-pit coal mines based on YOLOv12n.By replacing the backbone network with PP-LCNet, introducing a secondary improved MCADSA attention mechanism module, and adding an improved NWD loss function, the detection accuracy of the infrared image coal fire dataset has been improved, providing assistance for the intelligent inspection of early coal seam spontaneous combustion.

Key words: coal fire spontaneous combustion, UAV, infrared image, target detectio, YOLOv12

CLC Number:

P237

PANG Wenyu, ZHANG Xiaodong, ZHU Wei, TAO Qing. An early UAV coal fire infrared image target detection and recognition method in open-pit coal mines[J]. Bulletin of Surveying and Mapping, 2025, 0(10): 63-70.

References

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