CNNFET: Convolutional neural network feature Extraction Tools

Abstract

Neither machines nor even human can learn something not represented well enough. Therefore, feature extraction is one of the most important topics in machine learning. Deep convolutional neural networks are able to catch distinguishing features that can represent images or other digital signals. This makes them very popular in signal processing and especially in image processing community. Despite the proven success of these networks, training processes of them are often expensive in terms of time and required hardware capabilities. In this paper, a user-friendly standalone Windows application titled “Convolutional Neural Network Feature Extraction Tools” (CNNFET) is presented. The application consists of tools that extract features from image sets using certain layers of pre-trained CNNs, process them, perform classifications on them and export features for further processing in Matlab or the popular machine learning software Weka.