Meta features-based scale invariant OCR decision making using LSTM-RNN

Volume: 25, Issue: 2, Pages: 165 - 183
Published: Mar 20, 2018
Abstract
Urdu optical character recognition (OCR) is a complex problem due to the nature of its script, which is cursive. Recognizing characters of different font sizes further complicates the problem. In this research, long short term memory-recurrent neural network (LSTM-RNN) and convolution neural network (CNN) are used to recognize Urdu optical characters of different font sizes. LSTM-RNN is trained on formerly extracted feature sets, which are...
Paper Details
Title
Meta features-based scale invariant OCR decision making using LSTM-RNN
Published Date
Mar 20, 2018
Volume
25
Issue
2
Pages
165 - 183
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