YOLOv5

Cen Pan1, Qing Tao2, Hao Pei1

  • 1School of Intelligent Manufacturing and Modern Industry (School of Mechanical Engineering), Xinjiang University, Ürümqi, 830017, China.

Scientific reports
|January 14, 2025
PubMed
概括

这项研究引入了一种改进的深度学习方法,用于检测露天煤矿中的输送机置故障. 增强的YOLOv5模型通过准确的实时故障识别来确保更安全的采矿操作.

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