Research on Detection Method of Insulator Image Based on Improved Faster R-CNN

Abstract

This study proposes the use of Improved Faster Region-Convolutional Neural Network (R-CNN) in target detection for insulator images in power systems. Faster R-CNN is essentially a combination of the Fast R-CNN and the Regional Proposal Network (RPN). The Faster R-CNN method, which is being used today, is an extension and improvement of the Fast R-CNN. The Improved Faster R-CNN is particularly highly effective in the detection of occluded targets and those with different aspect ratios and scales. Through the various experiments conducted in the study, it has been demonstrated that the improved Faster R-CNN is highly effective in detecting insulator images with different scales and with different aspect ratios. Furthermore, the improved Faster R-CNN is also very effective in detecting mutually occluded insulator images.

Research on Key Algorithm for Sichuan Pepper Pruning Based on Improved Mask R-CNN

“…Partial JSON converted files.2.4. Mask R-CNN AlgorithmThe R-CNN (Region-based Convolutional Neural Network) series (R-CNN, Fast R-CNN, Faster R-CNN) is the pioneer in using deep learning for object detection[15]. Fast R-CNN and Faster R-CNN both follow the concept of R-CNN.…”