A fast learning algorithm for deep belief nets
Neural Computation
On the Class Imbalance Problem
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 04
Why Does Unsupervised Pre-training Help Deep Learning?
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Handwriting Recognition in Indian Regional Scripts: A Survey of Offline Techniques
ACM Transactions on Asian Language Information Processing (TALIP)
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We present a technique of using Deep Neural Networks (DNNs) for offline character recognition of Telugu characters. We construct DNNs by stacking Auto-encoders that are trained in a greedy layer-wise fashion in an unsupervised manner. We then perform supervised fine-tuning to train the entire network. We provide results on Consonant and Vowel Modifier Datasets using two and three hidden layer DNNs. We also construct an ensemble classifier to increase the classification performance further. We observe 94.25% accuracy for the two hidden layer network on Consonant data and 94.1% on Vowel Modifier Dataset which increases to 95.4% for Consonant and 94.8% for Vowel Modifier Dataset after combining classifiers to form an ensemble classifier of 4 different two hidden layer networks.