A Complex-Valued CNN for Different Activation Functions in Polarsar Image Classification

Abstract

With the successful application of convolution neural network (CNN) in image recognition field, this paper presents the complex-valued convolutional network (CV-CNN) using different activation functions. Then, four different activation functions of sigmoid, tanh, Leaky-ReLU and ELU were tested in typical polarimetric SAR image classification tasks. Experiments on benchmark datasets of Flevoland shows that CV-CNN using ELU activation function performs the best, with faster convergence speed and much higher recognition rate.