A snapshot of image pre-processing for convolutional neural networks: case study of MNIST

A snapshot of image pre-processing for convolutional neural networks: case study of MNIST

In the last five years, deep learning methods and particularly Convolutional Neural Networks (CNNs) have exhibited excellent accuracies in many pattern classification problems. Most of the state-of-the-art models apply data-augmentation techniques at the training stage. This paper provides a brief t...

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Bibliographic Details
Main Authors: Siham Tabik, Daniel Peralta, Andrés Herrera-Poyatos, Francisco Herrera
Format: Article
Language:English
Published: Atlantis Press 2017-01-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Classification
Deep learning
Convolutional Neural Networks (CNNs)
preprocessing
handwritten digits
data augmentation
Online Access:https://www.atlantis-press.com/article/25867315/view

Internet

https://www.atlantis-press.com/article/25867315/view

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