In this paper, a new approach of handwritten character recognition system with Artificial Neural Network (ANN) feedback is proposed. This recognition system is based on a neural recognition network and a neural feedba...
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In this paper, a new approach of handwritten character recognition system with Artificial Neural Network (ANN) feedback is proposed. This recognition system is based on a neural recognition network and a neural feedback network, the out put of which is used to modify the feature of the input pattern, thus preprocessing and recognition are integrated closely. Experiments show that this approach can make system performance very good and robust to environmental noise.
A new algorithm of handwritten character recognition based on feedback theory is proposed. We suggest this new method by adding confidence back-propagation and input modification on the neural network model, thus prep...
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A new algorithm of handwritten character recognition based on feedback theory is proposed. We suggest this new method by adding confidence back-propagation and input modification on the neural network model, thus preprocessing and recognition are integrated closely. Convergence of the algorithm is proved. Experiments show that it greatly reduced the system's error rate and was robust to environmental noise.
A novel method of relevance feedback is presented based on support vector machine learning in the content-based image retrieval system. A SVM classifier can be learned from training data of relevance images and irrele...
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ISBN:
(纸本)0780367251
A novel method of relevance feedback is presented based on support vector machine learning in the content-based image retrieval system. A SVM classifier can be learned from training data of relevance images and irrelevance images marked by users. Using the classifier, the system can retrieve more images relevant to the query in the database efficiently. Experiments were carried out on a large-size database of 9918 images. It shows that the interactive learning and retrieval process can find correct images increasingly. It also shows the generalization ability of SVM under the condition of limited training samples.
A novel multiscale method of vehicle license image segmentation based on wavelet transform is proposed. This analysis utilizes the local wavelet transform modulus maxima as the image edge at multiple scales, and combi...
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ISBN:
(纸本)9628576623
A novel multiscale method of vehicle license image segmentation based on wavelet transform is proposed. This analysis utilizes the local wavelet transform modulus maxima as the image edge at multiple scales, and combines the multiscale edge information. Then a template matching method is applied to segment the vehicle license image based on edge density analysis and character edge spatial feature after eliminating the long straight line noise. The approach integrates multiple scale edge information and overcomes the shortcoming of traditional single scale analysis. This advantage has special significance for the hazy image. Experimentation with about three hundred images obtained from a natural environment shows that the performance of this approach is better than the traditional method, especially for hazy images.
This paper introduces a Chinese spoken dialog system providing services for blind people through which. they can use computers. A description of the architecture of the dialog system is presented briefly and the way i...
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This paper introduces a Chinese spoken dialog system providing services for blind people through which. they can use computers. A description of the architecture of the dialog system is presented briefly and the way in which each component works is also explained. The key factor of such a dialog system is extraction of the intention of a user's utterance so as to make an appropriate response. To achieve this, a case grammar formalism was applied for semantic description and a robust spoken language parsing method based on case-frames was adopted to obtain the semantic interpretation of the input. It shows that this parsing method can tolerate errors of speech recognition and grammatical deviation of spoken language to some extent.
Openness is one of the features of modem robot controllers. Although many modeling technologies about how to model and develop open robot controllers have been discussed, the focus is always on some detail problems in...
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ISBN:
(纸本)0780370104
Openness is one of the features of modem robot controllers. Although many modeling technologies about how to model and develop open robot controllers have been discussed, the focus is always on some detail problems in some respects. While the relative complete modeling clews have never been discussed. In this paper, an initial modeling clew is presented. The corresponding contents including basic conceptions, modeling methods, requirement analysis, and testing strategies are discussed in detail.
The paper proposes a heuristic,attribute-based data mining algorithm,HGR(Heuristic Grouping), based on the newly-developed extension matrix *** the GROUP module is used to partition the positive examples of a specific...
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The paper proposes a heuristic,attribute-based data mining algorithm,HGR(Heuristic Grouping), based on the newly-developed extension matrix *** the GROUP module is used to partition the positive examples of a specific class in a given example set into different groups,and then the COMP module is used to find a conjunctive complex for each *** empirical comparison shows that the HGR's predicative accuracy is competitive with its immediate predecessor,the HCV algorithm,and the famous ID3-like algorithm C4.5.
Openness is one of the features of modern open robot controllers. The extending ability of control software is one of the important aspects related to openness. In order to overcome the limit of two existing extending...
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ISBN:
(纸本)0780370104
Openness is one of the features of modern open robot controllers. The extending ability of control software is one of the important aspects related to openness. In order to overcome the limit of two existing extending mechanisms, a composite extending mechanism which has mixed their merits is presented. On the foundations of this mechanism, a conceptual model of interface component in the extending mechanism is completed by the means of a hierarchical object-oriented Petri net (HOONet) according to the function analysis results of interface components, because HOONet can support a dynamic extending model and encompass the strong ability of abstraction and verification. This kind of interface component can support not only a communicating function but also a reliability function (information feedback function).
In order to achieve the competition tasks for multicooperating robots through learning, the paper discusses a kind of method that is designed for multi-agent systems (MAS), called the multi-reward fuzzy Q-learning alg...
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In order to achieve the competition tasks for multicooperating robots through learning, the paper discusses a kind of method that is designed for multi-agent systems (MAS), called the multi-reward fuzzy Q-learning algorithm (MRFQLA), which can be applied to the environment of the Robot World Cup Tournament (RoboCup). In MRFQLA., multiple reinforcement functions are established, based on the different characters of multi-agent systems. When the learning robot executes an action, these functions create multiple reinforcement signals that give the criteria of this action from different points of view. A Takagi-Sugeno (TS) model of a fuzzy inference system is built, which integrates these multiple rewards into one signal as the feedback of the learning robot. This method enhances the efficiency of learning because multiple rewards increase TD error and eliminates the conflict between the short-term target and the long-term one. Computer simulations in the RoboCup environment are shown and a discussion is given.
In the statistical approach to offline handwritten numeral recognition, we use the Gaussian mixture model (GMM) to approximate arbitrary class conditional probability density. For simplification, the GMM is assumed to...
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In the statistical approach to offline handwritten numeral recognition, we use the Gaussian mixture model (GMM) to approximate arbitrary class conditional probability density. For simplification, the GMM is assumed to be diagonal covariance matrices. In the case of the features of handwritten numerals being correlated statistically, a large number of mixture components are usually needed to obtain a good approximation. To solve this problem, the feature vectors are first transformed to the space spanned by the eigenvectors of the covariance matrix so that the correlation among the elements is reduced, namely orthogonal transformation. This GMM is defined as orthogonal Gaussian mixture model (OGMM). Finally, the effectiveness of this algorithm is demonstrated by applying it to the NIST database.
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