Multi-target detection of underground personnel based on an improved YOLOv8n model

Multi-target detection of underground personnel based on an improved YOLOv8n model

This study aims to address the complex challenges in monitoring underground personnel in hazardous areas, including uneven lighting, target scale inconsistency, and occlusion. An innovative multi-target detection algorithm, YOLOv8n-MSMLAS, was proposed based on the YOLOv8n network structure. The alg...

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Bibliographic Details
Main Authors: WEN Yongzhong, JIA Pengtao, XIA Mingao, ZHANG Longgang, WANG Weifeng
Format: Article
Language:zho
Published: Editorial Department of Industry and Mine Automation 2025-01-01
Series:Gong-kuang zidonghua
Subjects:
underground hazardous areas in coal mines
multi-target detection of underground personnel
yolov8n
multi-scale spatially enhanced attention mechanism
adaptive spatial feature fusion
lightweight hybrid local channel attention mechanism
Online Access:http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2024110035
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http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2024110035

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