An implementation of the backpropagation algorithm for images recognition

Authors

  • Trong Hien Dau Ho Chi Minh City University of Technology and Education, Vietnam

Corressponding author's email:

hiendt@hcmute.edu.vn

Keywords:

images recognition, Backpropagation, algorithm

Abstract

A neural network learning algorithm called Backpropagation is among the most effective approaches to machine learning when the data includes complex sensory input such as images. This document provides an implementation of the Backpropagation algorithm to recognize the images. To increase the speed of recognition color images are scaled to gray images. Note that the training process did not consist of a single call to a training function. Instead, the network was trained several times on various input ideal and noisy images. In this case training a network on different sets of noisy images forced the network to learn how to deal with noise, a common problem in the real world.

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References

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Published

28-09-2010

How to Cite

Dau, T. H. (2010). An implementation of the backpropagation algorithm for images recognition. Journal of Technical Education Science, 5(3), 18–20. Retrieved from https://jte.edu.vn/index.php/jte/article/view/795