Handwritten Digits Recognition using Deep Convolutional Neural Network: An Experimental Study using EBlearn
نویسنده
چکیده
In this paper, results of an experimental study of a deep convolution neural network architecture which can classify different handwritten digits using EBLearn library [1] are reported. The purpose of this neural network is to classify input images into 10 different classes or digits (0-9) and to explore new findings. The input dataset used consists of digits images of size 32X32 in grayscale (MNIST dataset [2]).
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عنوان ژورنال:
- CoRR
دوره abs/1307.3782 شماره
صفحات -
تاریخ انتشار 2013