Open AccessNeural Network Based Handwritten Character Recognition
Author(s) -
. Monika,
Monika Ingole,
Khemutai Tighare
Publication year - 2021
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/cseit217472
Subject(s) - character (mathematics) , computer science , artificial neural network , artificial intelligence , character recognition , point (geometry) , task (project management) , plan (archaeology) , neocognitron , intelligent character recognition , time delay neural network , speech recognition , natural language processing , machine learning , image (mathematics) , engineering , geometry , mathematics , systems engineering , archaeology , history
In this paper, an endeavor is made to perceive handwritten characters for English letters in order. The principle point of this task is to plan a master framework for, "HCR(English) utilizing Neural Network". that can viably perceive a specific character of type design utilizing the Artificial Neural Network approach. The handwritten character acknowledgment issue has become the most well-known issue in AI. Handwritten character acknowledgment has been a difficult space of examination, with the execution of Machine Learning we propose a Neural Network based methodology. Acknowledgment, precision rate, execution and execution time are a significant model that will be met by the technique being utilized.