Offline handwritten character classification of the same scriptural family languages by using transfer learning techniques
Satyasangram Sahoo, Prem Kumar B., R. Punitha Lakshmi · 2020
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.