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Benchmarking on offline Handwritten Tamil Character Recognition using convolutional neural networks
Published in Elsevier BV
Convolutional Neural Networks (CNN) are playing a vital role nowadays in every aspect of computer vision applications. In this paper we have used the state of the art CNN in recognizing handwritten Tamil characters in offline mode. CNNs differ from traditional approach of Handwritten Tamil Character Recognition (HTCR) in extracting the features automatically. We have used an isolated handwritten Tamil character dataset developed by HP Labs India. We have developed a CNN model from scratch by training the model with the Tamil characters in offline mode and have achieved good recognition results on both the training and testing datasets. This work is an attempt to set a benchmark for offline HTCR using deep learning techniques. This work have produced a training accuracy of 95.16% which is far better compared to the traditional approaches. © 2019 The Authors
About the journal
JournalData powered by TypesetJournal of King Saud University - Computer and Information Sciences
PublisherData powered by TypesetElsevier BV
Open AccessNo