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Yanxi Zhou, Shikai Zuo, Zhengxian Yang, Jinlong He, Jianwen Shi and Rui Zhang
Document image enhancement methods are often used to improve the accuracy and efficiency of automated document analysis and recognition tasks such as character recognition. These document images could be degraded or damaged for various reasons including ...
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Athita Onuean, Uraiwan Buatoom, Thatsanee Charoenporn, Taehong Kim and Hanmin Jung
In handwriting recognition research, a public image dataset is necessary to evaluate algorithm correctness and runtime performance. Unfortunately, in existing Thai language script image datasets, there is a lack of variety of standard handwriting types. ...
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Waleed Albattah and Saleh Albahli
Handwritten character recognition is a computer-vision-system problem that is still critical and challenging in many computer-vision tasks. With the increased interest in handwriting recognition as well as the developments in machine-learning and deep-le...
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Xuanming Fu, Zhengfeng Yang, Zhenbing Zeng, Yidan Zhang and Qianting Zhou
Deep learning techniques have been successfully applied in handwriting recognition. Oracle bone inscriptions (OBI) are the earliest hieroglyphs in China and valuable resources for studying the etymology of Chinese characters. OBI are of important histori...
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Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
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Joseph M. Ackerson, Rushit Dave and Naeem Seliya
Recurrent Neural Networks are powerful machine learning frameworks that allow for data to be saved and referenced in a temporal sequence. This opens many new possibilities in fields such as handwriting analysis and speech recognition. This paper seeks to...
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Angona Biswas,Md. Saiful Islam
Pág. 42 - 55
Background: Handwriting recognition becomes an appreciable research area because of its important practical applications, but varieties of writing patterns make automatic classification a challenging task. Classifying handwritten digits with a higher acc...
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Rosalina rosalina,Johanes Parlindungan Hutagalung,Genta Sahuri
Pág. pp. 161 - 168
These days there is a huge demand in ?storing the information available in paper documents into a computer storage disk?. Digitizing manual filled forms lead to handwriting recognition, a process of translating handwriting into machine editable text. The...
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Chang-Min Kim, Ellen J. Hong, Kyungyong Chung and Roy C. Park
Recently, demand for handwriting recognition, such as automation of mail sorting, license plate recognition, and electronic memo pads, has exponentially increased in various industrial fields. In addition, in the image recognition field, methods using ar...
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Ghazi Hussein Shakah
Pág. pp. 74 - 85
At the moment, all observed forms of communication are reduced either to a person-to-person scheme or person-to-device. But the Internet of Things (IoT) offers us a tremendous Internet future, in which will appear the communication type machine-machine (...
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