Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- th...
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Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.
While computing is entering a new phase in which CPU improvements are driven by the addition of multiple cores on a single chip, rather than higher frequencies. Parallel processing on these systems is in a primitive s...
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The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, ...
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The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism. Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.
With the fast development of World Wide Web, the quantity of web information is increasing in an unprecedented pace, a great many of which are generated dynamically from background databases, and can't be indexed ...
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With the fast development of World Wide Web, the quantity of web information is increasing in an unprecedented pace, a great many of which are generated dynamically from background databases, and can't be indexed by traditional search engine, so we call them Deep Web. For the heterogeneous and dynamic features of Deep Web sources, classifying the Deep Web source by domain effectively is a significant precondition of Deep Web sources integration. In this paper, we consider the visible features of Deep Web and Maximum Entropy approach, and then on the basis of binary classification, we propose a new multivariate classification approach based on Maximum Entropy towards Deep Web sources. In addition, we propose a Feedback algorithm to improve the accuracy of classification. An experimental evaluation over real Web data shows that, our approach could provide an effective and general solution to the multivariate classification of Deep Web sources.
Knowing semantic links among documents is the basis for intelligent applications over large-scale document resources. Discovering these semantic links with little human interference is a challenge issue. This paper pr...
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In this paper, we highlight the use of multimedia technology in generating intrinsic summaries of tourism related information. The system utilizes an automated process to gather, filter and classify information on var...
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ISBN:
(纸本)9781605580852
In this paper, we highlight the use of multimedia technology in generating intrinsic summaries of tourism related information. The system utilizes an automated process to gather, filter and classify information on various tourist spots on the Web. The end result present to the user is a personalized multimedia summary generated with respect to users queries filled with text, image, video and real-time news made retrievable for mobile devices. Preliminary experiments demonstrate the superiority of our presentation scheme to traditional methods.
This paper proposes a new pose estimation method based on the appearance of 2D head image. First, the 1D Gabor filters are used to extract the features on the raw images. Compared with the traditional 2D Gabor represe...
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In this paper, we propose an approach to automatic detection of semantic object. The method provides an effective content expression pattern for semantic analysis and retrieval of video. In the moving semantic object ...
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ISBN:
(纸本)9781424420209
In this paper, we propose an approach to automatic detection of semantic object. The method provides an effective content expression pattern for semantic analysis and retrieval of video. In the moving semantic object detection model, motion contrast is computed based on the planar motion (homography) between frames, which is estimated by applying RANSAC algorithm on point correspondences in the scene. In the semantic object detection model of static frame, the three features used are intensity, color and texture. Then a dynamic fusion technique is applied to combine these models. The automatic detection method can greatly decrease computation and be used in pervasive computing environment conveniently. Experimental results verify efficiency of proposed approach.
This paper presents a description for the ICT systems involved in the IWSLT 2008 evaluation campaign. This year, we participated in Chinese-English and English-Chinese translation directions. Four statistical machine ...
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Question classification is an important step in a question answering system, the accuracy rate of question classification has great impact to a question answering system's following module. This paper proposed a q...
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