Handwriting recognition using webcam for data entry

This paper presents the development of a system that is robust enough to recognize numerical handwritings with the lowest error. The first test was done with a neural network trained with only the Character Vector Module as its feature extraction method. A result that is far below the set point of t...

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Main Authors: Xiang, W.Y., Sebastian, P.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.31526 /
Published: Institute of Electrical and Electronics Engineers Inc. 2015
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957893479&doi=10.1109%2fCSPA.2015.7225626&partnerID=40&md5=a373adbab412189af38fa62f94e1baab
http://eprints.utp.edu.my/31526/
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