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Multiple Convolution Neural Networks for an Online Handwriting Recognition System

Authors:
Việt Dũng Phạm

Keywords: online handwriting; recognition; convolution; neural network.

Abstract:
This paper focuses on a specific word recognition technique for an online handwriting recognition system which uses Multiple Component Neural Networks (MCNN) as the exchangeable parts of the classifier. As the most recent of approaches, the system proceeds by segmenting handwriting words into smaller pieces (usually characters), which are recognized separately. The recognition results are then a composition of individually recognized characters. They are sent to the input of a word recognition module in turn to choose the most suitable one by applying some dictionary search algorithms. The proposed classifier overcomes obstacles and difficulties of traditional ones to large character classes. Furthermore, the proposed classifier also has expandable capacity, which can recognize other character classes by adding or changing component networks and built-in dictionaries dynamically.

Pages: 108 to 112

Copyright: Copyright (c) IARIA, 2014

Publication date: October 12, 2014

Published in: conference

ISSN: 2308-4537

ISBN: 978-1-61208-371-1

Location: Nice, France

Dates: from October 12, 2014 to October 16, 2014