International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 115

Vietnam | Information Technology | Volume 9 Issue 5, May 2020 | Pages: 678 - 682


Applied Convolutional Neural Network Algorithm in Handwritten Recognition for Digital Transformation

Nguyen Tuan, Duc-Hoang Chu, Nguyen Huu Phat

Abstract: In the paper, we exploit a small branch of identification handwritten recognition problem. That is the recognition of letters, handwritten characters for digital transformation. The information is transmitted digitally using handwriting capture camera. Images will then be processed and put into identification for information by text. In the paper, we propose the handwriting recognition algorithms based on convolutional neural network (CNN). The solution method is to separate character from handwritten letters taken by camera, and then applying recognition algorithm to determine what is the letter. The goal of the paper is to reduce the parameter of CNN. Experimental results using MATLAB show that the proposal algorithm improves up to 90 percent when selecting suitable learning factor of neural networks. The flexibility of this design allows it to extend to other languages easily.

Keywords: Recognition algorithm, contours, neural networks, handwritten, image processing



Citation copied to Clipboard!
Tuan, N., Chu, D., Phat, &N. H. (2020). Applied Convolutional Neural Network Algorithm in Handwritten Recognition for Digital Transformation. International Journal of Science and Research (IJSR), 9(5), 678-682. https://www.ijsr.net/getabstract.php?paperid=SR20510102040 https://www.doi.org/10.21275/SR20510102040

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