Offline handwritten character classification of the same scriptural family languages by using transfer learning techniques

Transfer Learning by using Convolutional Neural Network has shown its outstanding performance in large scale image classification. India is a multi-script and multilingual country. Out of all languages, Telugu and Kannada have shared almost similar structure characters. Offline character recognition of both handwriting characters is a challenging task. Different feature extraction models have been used in character recognition studies. Convolutional Neural Network is used as efficiently supervised feature vector extraction. Feature vectors from large scale pre-trained ImageNet or COCO were proved more efficient than other script datasets for better result. Fine-tuning model of transfer learning was used in the studies for comparison studies.