A RESEARCH ON IMPROVE HANDWRITTEN CHARACTER RECOGNITION BY USING CONVOLUTIONAL NEURAL NETWORK
| Author(s) | : | Hetal D. Anuvadiya, Prof.Ashutosh A. Abhangi |
| Institution | : | Computer Engineering, Noble Group of Institutions |
| Published In | : | Vol. 5, Issue 5 — May 2018 |
| Page No. | : | 20-25 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
For image recognition CNN is the most popular learning model. The features like weight sharing strategyand strong relations of the pixels of the image makes CNN best choice for image recognition. The feature extraction andclassification can be done simultaneously in deep learning models which has proved very needful compared to thetraditional methods. A promising recognition can be obtained by using CNN if we address to certain issues. So in CNNbased framework for handwritten character recognition that gives a better performance compared to other CNN basedrecognition methods.
Hetal D. Anuvadiya, Prof.Ashutosh A. Abhangi, “A RESEARCH ON IMPROVE HANDWRITTEN CHARACTER RECOGNITION BY USING CONVOLUTIONAL NEURAL NETWORK”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 5, pp. 20-25, May 2018.
