Creating edge detectors by evolutionary reinforcement learning

Abstract — In this article we present results from experiments where a edge detector was learned from scratch by EANT2, a method for evolutionary reinforcement learning. The detector is constructed as a neural network that takes as input the pixel values from a given image region—the same way that standard edge detectors do. However, it does not have any perimage parameters. A comparison between the evolved neural networks and two standard algorithms, the Sobel and Canny edge detectors, shows very good results. I