Research on Intrusion Object Recognition Method of Transmission Corridor Based on Deep Learning
In order to solve the problems of huge difference in size between intrusion objects and low contrast of some images in the process of online monitoring of transmission corridor,combining with the characteristics of foreign object images,a transmission line intrusion object recognition method based on object detection algorithm is proposed.Firstly,the intrusion object images of transmission corridor are collected,and the input images are enhanced by Retinex algorithm.In the part of object recognition,the improved EfficientDet algorithm is adopted as the main body,and the length-width ratio of the anchor frame is optimized by K-means clustering algorithm.Meanwhile,the gradient equalization mechanism is added into the loss function.Experimental results show that the mAP value of the improved algorithm increases from 83.72%to 87.12%,and it has excellent performance in the intrusion object recognition task.
万方数据
维普
