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Generating Realistic Chinese Handwriting Characters via Deep Convolutional Generative Adversarial Networks

  • Chenkai Gu
  • Jin Liu
  • Lei Kong
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 474)

Abstract

A person can hardly write a totally same handwriting character, more or less, there will be some tiny difference between each character. Usually, we use a neural network to generate handwriting characters, but each time we want this model to output a character, it will always the totally same. To solve this tiny different problem, we use a special neural network called DCGANs (deep convolutional generative adversarial networks). Experiments show that our method achieves good performance.

Keywords

Realistic characters Generate model DCGANs 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.College of Information EngineeringShanghai Maritime UniversityShanghaiChina
  2. 2.The Third Branch of Shanghai Administration InstituteShanghaiChina

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