RGB-W based Hazard Detection in Electric Power Communication Networks

Abstract

Hazard detection is an important computer vision area in electric power communication network.In this paper, we propose a hazard detection method in electric power communication network. This method turns the short-range wireless localization information into a confidence mask corresponding to the image size. The mask is able to be input into object detectors to revise confidence scores. The proposed method aims to increase the accuracy of the detections and alleviate the problems of false positives and false negatives. We design two kinds of confidence mask in order to find a better method to utilize the localization information. In addition, dataset containing specific scenes is collected to train and test the proposed method of hazard detection task in electric power communication network. Finally, this paper adopts various metrics to evaluate the effectiveness of the proposed method. The experiments demonstrate the feasibility and superiority of the proposed method in both theory and practice.