Research on Small Animal Target Detection Algorithm Based on YOLOv5
Aiming at the problems of high false alarm rate and low detection accuracy of small targets in existing sub-station intrusion detection algorithms,a substation intrusion small animal target detection algorithm based on improved YOLOv5 is proposed.The activation function in the SENet channel attention module and Convolutional Block Attention Mod-ule(CBAM)is improved to HardSwish function,and the improved SENet_H module and CBAM_H module is separately intro-duced into the backbone network and the neck network.Experimental results show that the improved small animal target detection algorithm outperforms the original YOLOv5 algorithm by 11.6%in precision,10.2%in recall,and 8.1%in mean average precision.
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