Implementation of Training Convolutional Neural Networks

TL;DR

This paper provides a detailed analysis of CNN algorithms, implements face recognition using CNN in Java, and explores parallel strategies to improve computational efficiency.

Contribution

It offers a comprehensive explanation of CNN processes, applies CNN to face recognition, and proposes a parallel computing strategy with efficiency analysis.

Findings

Implemented face recognition with CNN in Java

Analyzed parallel speedup and efficiency theoretically

Provided detailed CNN forward and backpropagation analysis

Abstract

Deep learning refers to the shining branch of machine learning that is based on learning levels of representations. Convolutional Neural Networks (CNN) is one kind of deep neural network. It can study concurrently. In this article, we gave a detailed analysis of the process of CNN algorithm both the forward process and back propagation. Then we applied the particular convolutional neural network to implement the typical face recognition problem by java. Then, a parallel strategy was proposed in section4. In addition, by measuring the actual time of forward and backward computing, we analysed the maximal speed up and parallel efficiency theoretically.