Publicado en Lecture Notes in Computer Science
Abstract
Nowadays,
Deep Learning is one of the most popular techniques which is used in
several fields like handwriting text recognition. This paper presents
our propose for a handwritten digit sequences recognition system. Our
system, based in two stage model, is composed by Convolutional Neural
Networks and Recurrent Neural Networks. Moreover, it is trained using
on-demand scheme to recognize numbers from digits of the MNIST dataset.
We will see that, with these training samples is not necessary segment
or normalize the input images. Average recognition results were on 88,6%
of accuracy in numbers of variable-length, between 1 and 10 digits.
This accuracy is independent on the number length. Moreover, in most of
the wrongly predicted numbers there was only one digit error.