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It is well known that the handwritten Chinese text recognition is a difficult problem since there are a large number of classes. In order to solve this problem, we proposed a whole new framework for unconstrained handwritten Chinese text recognition. The core module of the framework is the heterogeneous CNN trained by deep knowledge. The experimental results showed that our proposed method could achieve...
The segmentation of touching characters is still a challenging problem in offline Chinese handwriting recognition. One feasible solution is through the over-segmentation strategy which maintains a high recall of correct cuts between adjacent characters and a moderate level of redundant cuts within a single character. Previous redundant cut filtering methods rely on either pure heuristics or learned...
With the development of deep learning, many difficult recognition problems can be solved by deep learning models. For handwritten character recognition, the CNN is used the most. In order to improve the performance of CNN, many new models have been proposed and in which the relaxation CNN [35] is widely used. The relaxation CNN has more complicated structure than CNN while the recognition time is...
Automatic processing of large volume scanned Chinese bank statements is a urgent demand recently. Conventional methods can not well handle the following challenges of this problem: various layout styles, noises, and especially requirement of fast speed for large Chinese character set. This paper proposes a knowledge based table recognition method to meet fast speed requirement with good accuracy....
Because of the various appearance (different writers, writing styles, noise, etc.), the handwritten character recognition is one of the most challenging task in pattern recognition. Through decades of research, the traditional method has reached its limit while the emergence of deep learning provides a new way to break this limit. In this paper, a CNN-based handwritten character recognition framework...
Deep learning methods have recently achieved impressive performance in the area of visual recognition and speech recognition. In this paper, we propose a handwriting recognition method based on relaxation convolutional neural network (R-CNN) and alternately trained relaxation convolutional neural network (ATR-CNN). Previous methods regularize CNN at full-connected layer or spatial-pooling layer, however,...
Due to the ubiquity of web browsers and the dramatic development of dynamic web pages, web applications become the most popular computing model for providing services over the Internet. Unfortunately, this type of systems is vulnerable to the attacks issued by automated programs. CAPTCHA, a challenge-response test, is the most widely used mechanism to protect web application systems from attacks issued...
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