Online Handwriting Based Adult and Child Classification using Machine Learning Techniques

Author:

Shin Jungpil1,Hasan Md. Al Mehedi1,Maniruzzaman Md.1,Megumi Akiko2,Suzuki Akiko2,Yasumura Akira3

Affiliation:

1. The University of Aizu,School of Computer Science and Engineering,Aizuwakamastu, Fukushima,Japan

2. Kumamoto University,Graduate School of Social and Cultural Sciences,Kumamoto,Japan

3. Kumamoto University,Faculty of Humanities and Social Science,Kumamoto,Japan

Publisher

IEEE

Reference22 articles.

1. Gait analysis of gender and age using a large-scale multi-view gait database;makihara,2010

2. Gait-based categorization and feature analysis of gender and age;mannami;IEICE Transactions on Information and Systems,2009

3. Optimal linear and nonlinear solutions for least-square discriminant feature extraction;otsu;Proc Int Conf Pattern Recognition,1982

4. Classification of child and adult based on geometric features of the face using linear wavelets;mohan;International Journal of Signal and Image Processing,2010

5. Online handwriting recognition using support vector machine

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