Presentation 2020-12-22
Gender Estimation Method from Handwritten Characters Based on Deep Neural Network
Koting Wu, Sho Takizawa, Qiu Chen,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Humans can infer the gender of the writer from handwritten characters to a certain extent. In this paper, we propose a method for estimating the gender of a writer from Japanese handwritten characters using a deep neural network. We investigate various convolutional neural network architectures as a deep neural network, and the experimental results show that for the same two Japanese characters, the maximum gender estimation accuracy of 92% is obtained for handwritten characters when using VGG-16 network model.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Deep neural network / Handwritten characters / Gender identification / Gender estimation
Paper # HIP2020-56
Date of Issue 2020-12-15 (HIP)

Conference Information
Committee HIP
Conference Date 2020/12/22(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Shuichi Sakamoto(Tohoku Univ.)
Vice Chair Yuji Wada(Ritsumeikan Univ.) / Sachiko Kiyokawa(Nagoya Univ.)
Secretary Yuji Wada(NICT) / Sachiko Kiyokawa(NTT)
Assistant Hidetoshi Kanaya(Ritsumeikan Univ.) / Yuki Yamada(Kyushu Univ.)

Paper Information
Registration To Technical Committee on Human Information Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Gender Estimation Method from Handwritten Characters Based on Deep Neural Network
Sub Title (in English)
Keyword(1) Deep neural network
Keyword(2) Handwritten characters
Keyword(3) Gender identification
Keyword(4) Gender estimation
1st Author's Name Koting Wu
1st Author's Affiliation Kogakuin University(Kogakuin Univ.)
2nd Author's Name Sho Takizawa
2nd Author's Affiliation Kogakuin University(Kogakuin Univ.)
3rd Author's Name Qiu Chen
3rd Author's Affiliation Kogakuin University(Kogakuin Univ.)
Date 2020-12-22
Paper # HIP2020-56
Volume (vol) vol.120
Number (no) HIP-306
Page pp.pp.15-19(HIP),
#Pages 5
Date of Issue 2020-12-15 (HIP)