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DOI: 10.14569/IJACSA.2015.061115
PDF

Robust Convolutional Neural Networks for Image Recognition

Author 1: Hayder M. Albeahdili
Author 2: Haider A. Alwzwazy
Author 3: Naz E. Islam

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 11, 2015.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Recently image recognition becomes vital task using several methods. One of the most interesting used methods is using Convolutional Neural Network (CNN). It is widely used for this purpose. However, since there are some tasks that have small features that are considered an essential part of a task, then classification using CNN is not efficient because most of those features diminish before reaching the final stage of classification. In this work, analyzing and exploring essential parameters that can influence model performance. Furthermore different elegant prior contemporary models are recruited to introduce new leveraging model. Finally, a new CNN architecture is proposed which achieves state-of-the-art classification results on the different challenge benchmarks. The experimented are conducted on MNIST, CIFAR-10, and CIFAR-100 datasets. Experimental results showed that the results outperform and achieve superior results comparing to the most contemporary approaches.

Keywords: Convolutional Neural Network; Image recognition; Multiscale input images

Hayder M. Albeahdili, Haider A. Alwzwazy and Naz E. Islam, “Robust Convolutional Neural Networks for Image Recognition” International Journal of Advanced Computer Science and Applications(IJACSA), 6(11), 2015. http://dx.doi.org/10.14569/IJACSA.2015.061115

@article{Albeahdili2015,
title = {Robust Convolutional Neural Networks for Image Recognition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.061115},
url = {http://dx.doi.org/10.14569/IJACSA.2015.061115},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {11},
author = {Hayder M. Albeahdili and Haider A. Alwzwazy and Naz E. Islam}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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