Handwritten Character Recognition using Deep Learning
Bhargav Rajyagor1, Rajnish Rakhlia2

1Bhargav Rajyagor, Computer Science Department, Shree Brahmanand Institute Of Computer Science, Chaparda, Jungadh, India.
2Dr. Rajnish M. Rakholia, Associate Professor, S. S. Agraval Institute of Management and Technology, Navsari, GTU, India.
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5815-5819 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8608038620/2020©BEIESP | DOI: 10.35940/ijrte.F8608.038620

Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In day to day human life, handwritten documents are a general purpose for communication and restoring their information. In the field of computer science, character recognition using Deep Learning has more attention. DL has a massive set of pattern recognition tools that can apply to speech recognition, image processing, natural language processing and has a remarkable capability to find out a solution for complex machine learning problems. DL can focus on the specific feature of an image to character recognition for enhancing efficiency and accuracy. In this paper, we have presented a methods for handwritten character recognition using deep learning.
Keywords: Deep Learning, Segmentation, Recognition.
Scope of the Article: Deep Learning.