Handwritten Chinese Characters Recognition Based on Deep Learning

• Main Authors: Hsuan-Pei Lee, 李宣霈
• Other Authors: Jia-Ching Wang
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/435deh

碩士 === 國立中央大學 === 資訊工程學系 === 107 === Character recognition has already been a popular research field even when machine learning and deep learning haven’t been discussed frequently. For example, the technique of OCR(Optical Character Recognition) has already been quite mature. Along with the development of machine learning and deep learning these years, the research of character recognition has also made a great leap by using deep learning. English characters and digit recognition has already been quite mature. However, Chinese characters recognition hasn’t been as mature as English characters and digit recognition even if many researches were based on deep learning since the structure of Chinese characters is more complexed. In addition that the Chinese characters recognition is more difficult than English characters and digit recognition, due to the variance of the style of handwritten characters from one person to another person, handwritten characters is even more difficult to be detected or recognized if there are more than one style of handwritten characters on a piece of paper. Therefore, the purpose of this research is to find out whether the multi-style handwritten Chinese characters dataset can do better job on character detection and recognition compared to one-style or few-style handwritten Chinese characters dataset.