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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： M. D. Alexiuk N. J. Pizzi W. Pedrycz National Research Council Institute of Biodiagnostics Winnipeg MAN Canada

Analysis of functional magnetic resonance imaging data considers temporal correlation of hemodynamic intensity patterns to a known activation paradigm as well as spatial regions of similar responses. Default regions of interest are often obtained by analyst-directed thresholding of intensity or correlation values. This paper presents a method to determine data-driven regions of interest using image erosion to identify structurally significant components in the default regions, namely bridge voxels

关键词： Bridges Hemodynamics computational intelligence Magnetic resonance imaging Robustness Blood flow Clustering algorithms signal processing algorithms Biomedical signal processing Councils

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Arterial blood pressure system Modeling and signal analysis

Arterial blood pressure system Modeling and signal analysis

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International symposium on computational intelligence in Robotics and Automation

作者： Ebenal, Alexander J. Vasana, Susan Clinton, Corry Cox, Daniel Shine, Timothy Univ North Florida Sch Engn Jacksonville FL 32224 USA Mayo Clin Jacksonville Dept Anaesthesia Jacksonville FL 32224 USA

ISBN: (纸本)9781424407897

An approach to modeling and signal processing of the human heart is presented. First the anatomy of the heart is described and the anatomical functions performed are outlined. A preliminary model of the cardio-systemic circuit system is described. The aim is to further refine the model to correlate to measured responses and characterization of those responses. The APB signal analysis method is quantified and empirical examples are provided and analyzed.

关键词： Blood pressure

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M-channel nonlinear phase filter banks in image compression:: Structure, design, and signal extension

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ieee TRANSACTIONS ON signal processing 2007年第4期55卷 1339-1351页

作者： Uto, Toshiyuki Oka, Tomohiro Ikehara, Masaaki Ehime Univ Dept Comp Sci Fac Engn Matsuyama Ehime 790 Japan Keio Univ Dept Elect & Elect Engn Fac Sci & Technol Tokyo 108 Japan

This paper describes a transform coding technique based on M-channel perfect reconstruction filter banks with a nonlinear phase. In contrast with linear-phase filter banks, the nonlinearity provides an extra degree of freedom that can be used to design a more efficient transform. We present new lattice structures of paraunitary and perfect reconstruction (biorthogonal) filter banks, which can be implemented with a lower computational complexity and/or represented by a few free parameters, through the decomposition of the lattice blocks and the displacement across the delay block. We further discuss a smooth extension method for nonlinear-phase filter banks to obtain a nonexpansive transform. The promise of our proposed approaches is demonstrated through several design examples, extended signals and compression results.

关键词： image coding lattice structure nonlinear phase filter bank nonexpansive decomposition

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Hierarchical Face Clustering using SIFT image Features

Hierarchical Face Clustering using SIFT Image Features

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Panagiotis Antonopoulos Nikos Nikolaidis Ioannis Pitas Department of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

In this paper an algorithm to cluster face images found in video sequences is proposed. A novel method for creating a dissimilarity matrix using SIFT image features is introduced. This dissimilarity matrix is used as an input in a hierarchical average linkage clustering algorithm, which yields the clustering result. Three well known clustering validity measures are provided to asses the quality of the resulting clustering, namely the F measure, the overall entropy (OE) and the Gamma statistic. The final result is found to be quite robust to significant scale, pose and illumination variations, encountered in facial images

关键词： Face detection Clustering algorithms Humans Hidden Markov models signal processing algorithms Video sequences Face recognition Couplings Clustering methods Testing

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Life-long Semi-supervised Learning: Continuation of Both Learning and Recognition

Life-long Semi-supervised Learning: Continuation of Both Lea...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Youki Kamiya Toshiaki Ishii Osamu Hasegawa Department of Computational Intelligence and Systems Science Interdisciplinary Graduate Tokyo Institute of Technology Kanagawa Japan Imaging Science and Engineering Laboratory Tokyo Institute of Technology Japan

This paper presents a new method for continuous and incremental learning and recognition based on self-organized incremental neural networks. It is available in the fluctuating environment where the number of recognition classes cannot be defined. In this method, the learning process and recognition process are not separated. This method can acquire concept when multiple feature vectors of new input object come, and then can recognize it using previously acquired concept. We experiment an examples of life-long semi-supervised learning tasks in real world. In the result, the proposed method was able to learn and recognize 104 objects incrementally, non-stop, and in real time

关键词： Semisupervised learning Neural networks computational intelligence image recognition Humans Pattern recognition Data analysis signal processing Laboratories Training data

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A Multi-Window Stereo Vision Algorithm With Improved Performance at Object Borders

A Multi-Window Stereo Vision Algorithm With Improved Perform...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Jun Zhao Jayantha Katupitiya ARC Centre of Excellence for Autonomous Systems University of New South Wales Sydney NSW Australia

Conventional correlation based stereo vision algorithms have poor performance at object borders due to occlusion. In this paper, a new matching sequence has been introduced. To detect left object border, a left shifted window is used with right image as the reference image and process from left to right. This method gives excellent left object border detection while detection of right object border is poor. The right object borders can be detected with equal success using a right shifted window with left image as reference and process from right to left. The combination result is good detection at both object borders

关键词： Stereo vision Object detection signal processing algorithms Pixel computational intelligence Manufacturing processes Australia Performance evaluation Testing Shape

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A Novel Approach to Collect Training images from WWW for image Thesaurus Building

A Novel Approach to Collect Training Images from WWW for Ima...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Joohyoun Park Jongho Nang Department of Computer Science and Engineering Sogang University Seoul South Korea

This paper introduces a novel approach to change gathered images from WWW into training images to build an image thesaurus. The requirements for being training images are a large number of images and with highly relevant to a given concept. To fulfil these requirements, a system should be able to collect a large number of relevant images to a given concept from WWW by the proposed criterion of relevance to the concept for each image. Then, the irrelevant images would be filtered out by the modified hierarchical clustering method based on the weighted combination of 5 MPEG-7 visual descriptors and the proposed criterion of relevance to the concept for each cluster. Upon experimental results, the precision of the set of images generated by the proposed method is about 18% higher than that of the set of images generated by other methods

关键词： World Wide Web Thesauri image generation HTML image analysis MPEG 7 Standard image retrieval Content based retrieval computational intelligence signal processing

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Developing Metrics for Evolving a Musically Satisfying Result from a Population of Computer Generated Music Compositions

Developing Metrics for Evolving a Musically Satisfying Resul...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Kris Bryden Department of Music Iowa State University Ames IA USA

Creating a computational metric of the quality and musicality of a computer generated music composition is a challenging problem. This paper describes a possible way to develop numerically based metrics for standardizing the fitness evaluation of a population of computer generated music compositions. These metrics are based on assertions by music theorists about the dynamic forces within music that provides the music with a sense of motion and phrasing. The actions of several musical parameters are ranked according to the sense of intensity they produce. This process is applied to an acoustic music composition, and the values are then plotted on a graph. The composite curve from these values give the evaluator a sense of the patterns of lower and higher degrees of intensity, thus providing a sense of how well the music provides a sense of motion and phrasing

关键词： Neural networks Multiple signal classification signal generators Music Humans computational intelligence signal processing Application software Acoustic applications Calculus

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Voice conversion using nonlinear principal component analysis

Voice conversion using nonlinear principal component analysi...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： B. Makki S.A. Seyedsalehi N. Sadati M. Noori Hosseini Biomedical Engineering Department Amirkabir University of Technology슠 Tehran Iran Electrical Engineering Department Sharif University of Technology Tehran Iran

In the last decades, much attention has been paid to the design of multi-speaker voice conversion. In this work, a new method for voice conversion (VC) using nonlinear principal component analysis (NLPCA) is presented. The principal components are extracted and transformed by a feed-forward neural network which is trained by combination of genetic algorithm (GA) and back-propagation (BP). Common pre- and post-processing approaches are applied to increase the quality of the synthesized speech. The results indicate that the proposed method can be considered as a step towards multi-speaker voice conversion

关键词： Principal component analysis Speech synthesis Virtual colonoscopy image converters Neural networks Hidden Markov models Biomedical engineering computational intelligence signal processing Feedforward systems

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A Fingerprint Matching Scheme Based on Gradient Difference Compatibility

A Fingerprint Matching Scheme Based on Gradient Difference C...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Preeyakorn Tipwai Panudech Thipaksorn Suthep Madarasmi King Mongkut's University of Technology Thonburi Bangkok Thailand

This paper proposes a new minutiae-based fingerprint matching algorithm using a variation of the generalized Hough transform called MGHT, which allows variations in translation, rotation, scale, and some distortions of the fingerprints, with very low complexity. A simple local structure of the fingerprint is constructed to collect template data from a number of minutiae. The matching process is performed by voting for transformation parameters by using target fingerprint local structure to look up similar data in the template. The result with a strong peak in the parameter space is considered as a match. The algorithm is efficient, precise, and robust to noise. The test results on several images demonstrate the effectiveness of this fingerprint matching method

关键词： Fingerprint recognition signal processing algorithms Fingers computational intelligence Biomedical signal processing Distortion Voting Noise robustness Testing Biometrics

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