Implementation of Training Convolutional Neural Networks
Computer Vision and Pattern Recognition
2015-06-05 v2 Machine Learning
Neural and Evolutionary Computing
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.
Cite
@article{arxiv.1506.01195,
title = {Implementation of Training Convolutional Neural Networks},
author = {Tianyi Liu and Shuangsang Fang and Yuehui Zhao and Peng Wang and Jun Zhang},
journal= {arXiv preprint arXiv:1506.01195},
year = {2015}
}
Comments
10 pages, 6 figures