Edge Detection with ResNet

Abstract

Edge detection in computer vision is essential for higher-level vision tasks such as shape matching, visual salience, image segmentation, and object recognition. The methods based on deep learning are among the methods that have been proposed to increase accuracy, which is highly popular. In this paper, a method for edge detection with one of the deep architectures that have high accuracy is proposed. The results show that the F-measure for the proposed method with ResNet architecture has improved compared to other compared methods.