Advances in Chinese Document and Text Processing
Nonfiction, Computers, Advanced Computing, Natural Language Processing, Application Software, General Computing
| Author: | Cheng-Lin Liu, Yue Lu | ISBN: | 9789813143692 |
| Publisher: | World Scientific Publishing Company | Publication: | March 14, 2017 |
| Imprint: | WSPC | Language: | English |
| Author: | Cheng-Lin Liu, Yue Lu |
| ISBN: | 9789813143692 |
| Publisher: | World Scientific Publishing Company |
| Publication: | March 14, 2017 |
| Imprint: | WSPC |
| Language: | English |
The book is a collection of invited chapters by experts in Chinese document and text processing, and is part of a series on Language Processing, Pattern Recognition, and Intelligent Systems. The chapters introduce the latest advances and state-of-the-art methods for Chinese document image analysis and recognition, font design, text analysis and speaker recognition. Handwritten Chinese character recognition and text line recognition are at the core of document image analysis (DIA), and therefore, are addressed in four chapters for different scripts (online characters, offline characters, ancient characters, and text lines). Two chapters on character recognition pay much attention to deep convolutional neural networks (CNNs), which are widely used and performing superiorly in various pattern recognition problems. A chapter is contributed to describe a large handwriting database consisting both online and offline characters and text pages. Postal mail reading and writer identification, addressed in two chapters, are important applications of DIA. The collection can serve as reference for students and engineers in Chinese document and text processing and their applications.
Contents:
- Characteristics of English, Chinese, and Arabic Typefaces (Ching Y Suen, Shima Nikfal, Bing Zhang & Jehan Janbi)
- Chinese Handwriting Database Building and Benchmarking (Cheng-Lin Liu, Fei Yin, Da-Han Wang, Qiu-Feng Wang, Liang Xu & Xu-Yao Zhang)
- CNNBased Handwritten Character Recognition (Song Wang, Li Chen, Chunpeng Wu, Wei Fan, Jun Sun & Satoshi Naoi)
- Online Handwritten Chinese Character Recognition: From a Bayesian Approach to Deep Learning*(Lianwen Jin, Weixin Yang, Ziyong Feng & Zecheng Xie)*
- Historical Chinese Character Recognition Using Transfer Learning (Liangrui Peng & Jixiong Feng)
- Handwritten Chinese Text Line Recognition (Qiu-Feng Wang, Fei Yin & Cheng-Lin Liu)
- Handwritten Chinese Address Recognition for Postal Automation (Shujing Lu, Xiaohua Wei, Xiao Tu & Yue Lu)
- Off-line Text-independent Writer Identification for Chinese Handwriting (Yu-Jie Xiong & Yue Lu)
- Chinese Word Segmentation, Syntactic Parsing and Discourse Analysis*(Man Lan & Yuanbin Wu)*
- Speaker Recognition: Deep Neural Networks Approach (Xin He & Lekai Huang)
Readership: Students and researchers in Chinese document and text processing.
The book is a collection of invited chapters by experts in Chinese document and text processing, and is part of a series on Language Processing, Pattern Recognition, and Intelligent Systems. The chapters introduce the latest advances and state-of-the-art methods for Chinese document image analysis and recognition, font design, text analysis and speaker recognition. Handwritten Chinese character recognition and text line recognition are at the core of document image analysis (DIA), and therefore, are addressed in four chapters for different scripts (online characters, offline characters, ancient characters, and text lines). Two chapters on character recognition pay much attention to deep convolutional neural networks (CNNs), which are widely used and performing superiorly in various pattern recognition problems. A chapter is contributed to describe a large handwriting database consisting both online and offline characters and text pages. Postal mail reading and writer identification, addressed in two chapters, are important applications of DIA. The collection can serve as reference for students and engineers in Chinese document and text processing and their applications.
Contents:
- Characteristics of English, Chinese, and Arabic Typefaces (Ching Y Suen, Shima Nikfal, Bing Zhang & Jehan Janbi)
- Chinese Handwriting Database Building and Benchmarking (Cheng-Lin Liu, Fei Yin, Da-Han Wang, Qiu-Feng Wang, Liang Xu & Xu-Yao Zhang)
- CNNBased Handwritten Character Recognition (Song Wang, Li Chen, Chunpeng Wu, Wei Fan, Jun Sun & Satoshi Naoi)
- Online Handwritten Chinese Character Recognition: From a Bayesian Approach to Deep Learning*(Lianwen Jin, Weixin Yang, Ziyong Feng & Zecheng Xie)*
- Historical Chinese Character Recognition Using Transfer Learning (Liangrui Peng & Jixiong Feng)
- Handwritten Chinese Text Line Recognition (Qiu-Feng Wang, Fei Yin & Cheng-Lin Liu)
- Handwritten Chinese Address Recognition for Postal Automation (Shujing Lu, Xiaohua Wei, Xiao Tu & Yue Lu)
- Off-line Text-independent Writer Identification for Chinese Handwriting (Yu-Jie Xiong & Yue Lu)
- Chinese Word Segmentation, Syntactic Parsing and Discourse Analysis*(Man Lan & Yuanbin Wu)*
- Speaker Recognition: Deep Neural Networks Approach (Xin He & Lekai Huang)
Readership: Students and researchers in Chinese document and text processing.
