Handwriting Character Recognition using Vector Quantization Technique

Handwriting Character Recognition using Vector Quantization Technique

This paper seeks to explore Learning Vector Quantization (LVQ) processing stage to recognize The Buginese Lontara script from Makassar as well as explaining its accuracy. The testing results of LVQ obtained an accuracy degree of 66.66 %. The most optimal variant of network architecture in the recogn...

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Bibliographic Details
Main Authors: Haviluddin Haviluddin, Rayner Alfred, Ni’mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi
Format: Article
Language:English
Published: Universitas Negeri Malang 2019-12-01
Series:Knowledge Engineering and Data Science
Online Access:http://journal2.um.ac.id/index.php/keds/article/view/9869

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