Proceedings ArticleDOI
Bengali handwritten character recognition using deep convolutional neural network
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TLDR
A convolutional deep model to recognize Bengali handwritten characters is proposed that first learnt a useful set of features by using kernels and local receptive fields, and then it has employed densely connected layers for the discrimination task.Abstract:
Handwritten character recognition is a nontrivial task as it seeks to recognize the correct class for user independent handwritten characters. This problem becomes even more challenging for a highly stylized, morphologically complex, and potentially juxtapositional characters comprising language like Bengali. As a result, the improvements over the years in Bengali character recognition are significantly less as compared to the other languages. In this paper, we propose a convolutional deep model to recognize Bengali handwritten characters. We first learnt a useful set of features by using kernels and local receptive fields, and then we have employed densely connected layers for the discrimination task. Our system has been tested on BanglaLekha-Isolated dataset. It achieves 98.66% accuracy on numerals (10 character classes), 94.99% accuracy on vowels (11 character classes), 91.60% accuracy on compound letters (20 character classes), 91.23% accuracy on alphabets (50 character classes), and 89.93% accuracy on almost all Bengali characters (80 character classes). Most of the errors incurred by our model in recognition task are due to extreme proximity in shapes among characters. A significant number of errors was caused by the mislabeled, irrecoverably distorted, and illegal data examples.read more
Citations
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Proceedings ArticleDOI
Bangla Handwritten Character Recognition using Convolutional Neural Network with Data Augmentation
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TL;DR: A process of Handwritten Character Recognition to recognize and convert images of individual Bangla handwritten characters into electronically editable format is proposed, which will create opportunities for further research and can also have various practical applications.
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Devanagari Handwritten Character Recognition using fine-tuned Deep Convolutional Neural Network on trivial dataset
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