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IEEE International Conference on Cognitive Informatics

作者： Zhongzhi Shi Youping Huang Jian Zhang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)0769521908

Perceptual learning happens at the perceptual level. We combine holism and reductionism to research perception learning. Based on information geometry the paper presents a neural field model which is used to understand the transformation mechanism, dynamical behavior, capability and limitation of neural network models, by the study of globally topological and geometrical structure on parameter spaces of neural networks. We discuss neural field representation, fractal learning principle, topology approximation correction learning and the dualistic correction learning algorithm. Finally the paper gives conclusions and points out future research topics.

关键词： Solid modeling Biological neural networks information geometry Manifolds information processing Fractals Network topology Approximation algorithms Cognitive informatics Humans

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Formal data model and algebra for resource sharing in grid

Formal data model and algebra for resource sharing in grid

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2nd International Workshop on Grid and Cooperative computing, GCC 2003

作者： Sheng, Qiujian Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704-28 Beijing100080 China Graduate School of the Chinese Academy of Sciences Beijing China

ISBN: (纸本)3540219935

Management of various complex resources is an important issue to be well done, in order to fulfill the potential of Grid. In this paper, we propose a formal data model and algebra for resource sharing in the Grid. In the model, domain ontology knowledge is described within knowledge schema and domain background knowledge is captured in integrity constrain rules. A query algebra is defined to manipulate the modeled resource base. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Algebra

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Future interconnection environment - Dream, principle, challenge and practice : Keynote

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3129卷 13-22页

作者： Zhuge, Hai China Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology China

Networks and flows are everywhere in society, nature and virtual world organizing versatile resources and behaviors. Breaking boundaries, this keynote establishes a scenario of the future interconnection environment - a large-scale, autonomous, live, sustainable and intelligent network environment where society, nature, and the environment harmoniously co-exist, cooperatively work and evolve. It automatically senses and collects useful information from the nature, transforms raw information into resources in the environment, and organizes resources in semantic rich normal forms that can be easily understood by both machine and human. Geographically dispersed people and resources can work in cooperation to accomplish tasks and solve problems by actively participating material flows, energy flows, technology flows, information flows, knowledge flows and service flows in the environment through roles and machines, improving the environment and the nature. Parameters, characteristics and principles of the environment are proposed from the system methodology point of view. A case study on a live semantic link network under a reference model of the environment is presented. As a practice, the advanced architecture and technology used in China Knowledge Grid e-science environment IMAGINE-1 is introduced. © Springer-Verlag 2004.

关键词： e-Science

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A Multi-layers Neural Network Model based on Characteristics of Ganglions' Receptive Fields in Retina and an Algorithm for Watchfulness-keeping

A Multi-layers Neural Network Model based on Characteristics...

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The Third Asian Conference on Vision (ACV2004)

作者：危辉陆汝钤 Department of Computer Science Lab of Algorithm for Cognitive Model Brain Science Research Center Fudan University Shanghai 200433 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100080 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100080 China

Machine vision is an active branch of Artificial Intelligence. An important problem in this area is the balance among efficiency, accuracy and huge computing. The visual system of human can keep watchfulness to the perimeter of visual field while at same time their central attention is focused to the center of visual field for fine information processing. This mechanism of computing resource assignment could ease the demand for huge and complex hardware structure. Therefore designing computer model based on biological visual

关键词： A Multi-layers Neural Network Model based on Characteristics of Ganglions Receptive Fields in Retina and an Algorithm for Watchfulness-keeping Model

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An algebraic multi-class classification method

An algebraic multi-class classification method

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qing He Zhen-Yan Liu Zhong-Zhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China School of Software Beijing Institute of Tèchnology Beijing China

ISBN: (纸本)0780384032

An algebraic multi-class classification method AHSC, i.e., algebraic hyper surface classification, is proposed. The separating algebraic hyper surface of two-class data may be directly constructed by a single polynomial in theory, but it is too difficult to separate multi-class data by a single polynomial even though the polynomial is multivalued. AHSC can be used for classifying multi-class data by integrating a series of polynomial networks based on binary numbers, which are used for labeling the classes of samples. The problem that multi-class data cannot always be separated by a single polynomial is solved by AHSC. Moreover, using an adaptive method can choose the order of polynomial. The experimental results show that the new method can efficiently and accurately classify multi-class and high dimension data.

关键词： Polynomials Machine learning Error correction codes Mathematical model Neurons Vectors Helium information processing Computers Electronic mail

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Amplitude spectrum-based gait recognition

Amplitude spectrum-based gait recognition

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International Conference on Automatic Face and Gesture Recognition

作者： Guoying Zhao Rui Chen Guoyi Liu Hua Li Graduate School of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)0769521223

Gait is a biometric feature and identification of people from gait captured on video that has become a challenging problem in computer vision. A recognition method based on amplitude spectrum (Fourier spectrum) of frequency domain is proposed. Fourier spectrum reflects the frequency feature of person's pose in the current frame. After getting the period and key poses through the whole sequence according to the height of centroid and the amplitude value in frequency domain, we extract 5D features from the sequence including four amplitude values corresponding to four key poses image and the proportion of body. Finally, three measures are applied to evaluate our algorithm. Experiments result on USF dataset show that our method is insensitive to many changes condition of background, lighting, clothing, walking speed, segment noise and so on. For we implement gait recognition according to the discriminant analysis, the result to some extent is robust to the variation of viewpoint and cloth and recognition rate is satisfying.

关键词： Biometrics Face recognition Image recognition Frequency domain analysis Clothing Legged locomotion Iris Fingerprint recognition Humans Surveillance

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A fast VLSI architecture for two-dimensional discrete wavelet transform based on lifting scheme

A fast VLSI architecture for two-dimensional discrete wavele...

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2004 7th International Conference on Solid-State and Integrated Circuits technology Proceedings, ICSICT 2004

作者： Xiong, Chengyi Tian, Jinwen Liu, Jian Institute of Pattern Recognition and Artificial Intelligence Key Laboratory of Eduaction Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China College of Electronic Information Engineering South-Center University for Nationalities Wuhan 430074 China

This paper proposes a novel fast architecture for two-dimensional discrete wavelet transform by using lifting scheme. The parallel and embedded decimation techniques are employed to optimize the architecture, which is mainly composed of two horizontal filter modules and one vertical filter module, working in parallel and pipeline fashion with 100% hardware utilization. The architecture is designed to generate two outputs at one working clock cycle, with every two subbands coefficients alternately. The total time of computing J levels of decomposition for N×N image is approximately 2N2(I-4 J)/3 clock cycles. In comparison with the other devices reported in previous literature, the design has many advantages including lower hardware complexity and area and power efficient. The design is also fast, regular and simple, as well as well suited for VLSI implementation. © 2004 IEEE.

关键词： VLSI circuits

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A survey of subpixel object localization for image measurement

A survey of subpixel object localization for image measureme...

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International Conference on information and Automation (ICIA)

作者： Xiaojia Wang Jun Gao Lei Wang Laboratory of Image Information Processing Hefei University of Technology Anhui China Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China

ISBN: (纸本)0780386299

Subpixel object localization plays the key role to advance the precision of image measurement system. In this paper, the main idea of the subpixel algorithm and the imaging process as the physical background, is introduced first. Then various subpixel algorithms classified by their location object are analyzed. In the end of paper, the research and prospect of subpixel is proposed.

关键词： Optical imaging Optical sensors Image sensors Sensor systems Charge coupled devices Pixel Signal processing algorithms Charge-coupled image sensors Surface waves Optical surface waves

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A computational model of object-based selective visual attention mechanism in visual information acquisition

A computational model of object-based selective visual atten...

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International Conference on information and Automation (ICIA)

作者： Tianfu Wu Jun Gao Qin Zhao Laboratory of Image Information Processing Hefei University of Technology Anhui China Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China

ISBN: (纸本)0780386299

A computational model of object-based selective visual attention is introduced. What are the units of selective attention is always the focus of selective attention. Most existing computational model of selective attention is space-based, but more and more neuroscience experiments indicate that it is object-based. For object-based attention, how to define "object" is the biggest difficulty and it is generally accepted that the "object" refers to "perceptual object" which is created by Gestalt rules. However, Gestalt rules are very difficult to be calculated in images. The model presented in this paper is comprised of two independent components. One component is object-based segmentation by using perceptual color cues, the other is the generation of a object-based saliency-map in terms of the inhibition of return mechanism. Lastly, the results of experiments show that the model is valid.

关键词： Computational modeling Focusing Computational intelligence Machine intelligence information processing Space technology Neuroscience Image segmentation Retina Biology

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The grey theory and the preliminary probe into information acquisition technology

The grey theory and the preliminary probe into information a...

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International Conference on information and Automation (ICIA)

作者： Qin Zhao Jun Gao Tianfu Wu Lu Lu Laboratory of Image Information Processing Hefei University of Technology Anhui China Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China

ISBN: (纸本)0780386299

The grey theory, one of the methods that are used to study uncertainty, is superior in theoretical analysis of systems with imprecise information and incomplete samples. In this paper we summarize the principles of the theory and its modeling schemes in prediction and diagnosis, and review its practical applications so as to give some heuristic guidelines for improving the information acquisition technology.

关键词： Probes Predictive models History Differential equations information analysis Guidelines Aerodynamics information processing Machine intelligence Uncertainty

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