# Implementation of Training Convolutional Neural Networks

arXiv: https://arxiv.org/abs/1506.01195 · HTML: https://mlsanity.com/paper/1506.01195/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2015.

## Built on by (most cited first, 2 of 2)

- [Accuracy Improvement for Fully Convolutional Networks via Selective Augmentation with Applications to Electrocardiogram Data](https://mlsanity.com/paper/2104.12284/) (2021)
- [Deep Multi-Branch CNN Architecture for Early Alzheimer's Detection from Brain MRIs](https://mlsanity.com/paper/2210.12331/) (2022)

## Abstract (arXiv)

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.