Performance Analysis of Artificial Neural Network Algorithms for Automatic Handwritten Devanagari Text Generation in Marathi Styles

Abstract

 Devanagari content extensively utilized the critical content in India. Generally that content can be utilized to compose Sanskrit, Nepali, Marathi and Hindi dialects. With the expanded interest, investigation and globalization of advanced Devanagari records, diverse printed and manually written archive acknowledgment systems have included since most recent 20 years. The means that are engaged with character acknowledgment and content age are pre-handling, division, include extraction and order. There are various methods for devanagiri content like K Nearest Neighbour (KNN), Artificial Neural Network (ANN) and Support Vector Machine (SVM). The ANN strategy is actualized inside the python stage and it contrasted and the Artificial Neural Network (ANN). The presentation of the proposed strategy is broke down with factual estimations of exactness, accuracy and review.