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IMAGE COMPRESSION BY VARIABLE BLOCK TRUNCATION CODING WITH OPTIMAL THRESHOLD

IEEE TRANSACTIONS ON SIGNAL PROCESSING 1991年第1期39卷 208-212页

作者： KAMEL, M SUN, CT GUAN, L Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

In this correspondence we propose two modifications to the block truncation coding techniques. The first modification allows the partitioning of the image into variable size blocks rather than fixed size. The second m... 详细信息

关键词： Image coding Mean square error methods Pixel Image reconstruction Sun Vector quantization Tail pattern analysis machine intelligence System analysis and design

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CLASSIFICATION OF IMPEDANCE TRACES

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IEEE TRANSACTIONS ON systems MAN AND CYBERNETICS 1987年第4期17卷 707-713页

作者： SHEN, HC PILKEY, RM Department of Systems Design Engineering Pattern Analysis and Machine Intelligence Group University of Waterloo Waterloo ONT Canada

In the field of electronic fault detection much of the evaluation is performed by a human operator using a visual inspection system. One such system displays the current versus voltage (I-V) characteristics, referred to as the impedance trace, of the electronic component under test. The shape of the impedance trace indicates the integrity of the component. The subjectivity and poor repeatability of the visual inspection have been identified as major deficiencies in the existing systems. A microprocessor-based system has been proposed to store and provide a quantitative classification of the impedance traces. The primary objective of this system is to provide an efficient automated system for classifying the impedance traces of different electronic components. Thus three trace representations and two classification schemes are proposed, based upon techniques developed in the field of pattern recognition. An experiment contrasts the different classification approaches. A Fourier series representation, combining both magnitude and phase features, was determined to provide the best overall performance when used in conjunction with a developed distance measure.

关键词： Impedance Inspection Electronic components Fault detection Performance evaluation Humans Displays Voltage Electronic equipment testing System testing

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DYKOR - A METHOD FOR GENERATING THE CONTENT OF EXPLANATIONS IN KNOWLEDGE systems

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KNOWLEDGE-BASED systems 1994年第3期7卷 177-188页

作者： LOPEZSUAREZ, A KAMEL, M Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo Waterloo Ontario Canada N2L 3G1

The paper presents a methodology for improving the organization of knowledge bases and demonstrates its application for generating the content of explanations. The DyKOr (Dynamic Knowledge Organization) method combines information that is usually available through execution traces with existing domain knowledge using techniques from machine learning including knowledge compilation, explanation-based learning, and conceptual clustering. These techniques allow the separation of the knowledge needed to solve a problem from that which is not required, and the identification of information that is related to the problem but is not explicitly stated. Thus, the analysis performed through the methodology can considerably improve the quality and content of explanations. The paper describes the implementation of the methodology and how it can be integrated into typical rule-based expert systems. Illustrations of how the method can be used to produce the content for explanations are presented in the context of typical consultation and problem solving expert systems. A discussion of how the information produced by the method can be used to prepare explanations for users with different levels of expertise is also presented.

关键词： KNOWLEDGE ORGANIZATION RULE-BASED systems EXPLANATION-BASED LEARNING

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Increasing object recognition rate using reinforced segmentation

Increasing object recognition rate using reinforced segmenta...

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2006 IEEE International Conference on Image Processing, ICIP 2006

作者： Sahba, Farhang Tizhoosh, Hamid R. Salama, Magdy M. A. Systems Design Engineering Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Waterloo ON Canada Electrical and Computer Engineering Pattern Analysis and Machine Intelligence Laboratory University of Waterloo 200 University Ave W Waterloo ON Canada

ISBN: (纸本)1424404819

In this paper a new approach to object extraction and recognition based on reinforcement learning is presented. We use this novel idea as a method to optimally segment the image and increase the recognition rate. The success rate is compared with a classical approach. Preliminary results demonstrate increase in recognition rate. ©2006 IEEE.

关键词： Image segmentation

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Shape-based image retrieval applied to trademark images

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International Journal of Image and Graphics 2002年第3期2卷 375-393页

作者： El Badawy, Ossama Kamel, Mohamed Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada

We propose a new shape-based, query-by-example, image database retrieval method that is able to match a query image to one of the images in the database, based on a whole or partial match. The proposed method has two key components: the architecture of the retrieval and the features used. Both play a role in the overall retrieval efficacy. The proposed architecture is based on the analysis of connected components and holes in the query and database images. The features we propose to use are geometric in nature, and are invariant to translation, rotation and scale. Each of the suggested three features is not new per se, but combining them to produce a compact and efficient feature vector is. We use hand-sketched, rotated and scaled query images to test the proposed method using a database of 500 logo images. We compare the performance of the suggested features with the performance of the moment invariants (a set of commonly-used shape features). The suggested features match the moment invariants in rotated and scaled queries and consistently surpass them in hand-sketched queries. Moreover, results clearly show that the proposed architecture significantly increases the performance of the two feature sets. © 2002 World Scientific Publishing Company.

关键词： Database systems

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Automatic image registration using virtual circles

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International Journal of Image and Graphics 2004年第2期4卷 281-299页

作者： Alhichri, Haikel S. Kamel, Mohamed Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo 200 University Ave. West WaterlooONN2L3G1 Canada University of Waterloo Canada

The main contribution of this work is a novel set of image features called the virtual circles and their use in the registration of images under similarity transformations. A virtual circle is a circle with maximal radius encompassing a background area that does not contain edge points. It has many useful properties such as its radius, and its dominant edge direction for example, which can be utilized for efficient registration. Furthermore, virtual circles are frequent and can be extracted efficiently with the help of the distance transform from many types of images. We have tested the new virtual circles method in the registration of 66 pairs of images, half of which are printed labels and the other half are indoor scenes. Experimental results have shown that this method has a linear complexity in terms of the number of pixels. It is also highly automatic, because it has a small number of parameters, which almost never need to be changed throughout the experiments. © 2004 World Scientific Publishing Company.

关键词： Image registration

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Document classification using phrases

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Joint IAPR 9th International Workshop on Structural and Syntactic pattern Recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in pattern Recognition, SPR 2002

作者： Bakus, Jan Kamel, Mohamed Pattern Analysis and Machine Intelligence Lab Department of Systems Design Engineering University of Waterloo WaterlooON Canada

ISBN: (纸本)3540440119

This paper presents a Bayes document classifier using phrases as *** e phrases are extracted using a grammar that iteratively applies the rules to the sequence of words in the document. This grammar is generated from a training set using statistical word association. W e report an improvement in the classification over the "bag of words" representation. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Classification (of information)

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Improving the convergence of backpropagation by opposite transfer functions

Improving the convergence of backpropagation by opposite tra...

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IEEE International Joint Conference on Neural Network

作者： Ventresca, Mario Tizhoosh, Hamid R. Pattern Analysis and Machine Intelligence (PAMI) Laboratory Systems Design Engineering Department University of Waterloo Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9780780394902

The backpropagation algorithm is a very, popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately learn the task is considerable. Many existing approaches have improved the convergence rate by altering the learning algorithm. We present a simple alternative approach inspired by opposition-based learning that simultaneously considers each network transfer function and its opposite. The effect is an improvement in convergence rate and over traditional backpropagation learning with momentum. We use four common benchmark problems to illustrate the improvement in convergence time.

关键词： Multilayer neural networks

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Particle swarm clustering ensemble 08

Particle swarm clustering ensemble

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10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008

作者： Ahmadi, Abbas Karray, Fakhri Kamel, Mohamed Pattern Analysis and Machine Intelligence Lab. Department of Systems Design Engineering University of Waterloo 200 University Avenue West Waterloo ON Canada

ISBN: (纸本)9781605581309

Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recently. In this paper, an ensemble of particle swarm clustering algorithms is proposed. That is, the members of the ensemble are based on the cooperative swarms clustering approaches. The performance of the proposed particle swarm clustering ensemble is evaluated using different data sets and is compared to that of other clustering techniques.

关键词： Particle swarm optimization (PSO)

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Topic discovery from text using aggregation of different clustering methods 15th

Topic discovery from text using aggregation of different clu...

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15th Conference of the Canadian Society for Computational Studies of intelligence, AI 2002

作者： Ayad, Hanan Kamel, Mohamed Pattern Analysis and Machine Intelligence Lab Systems Design Engineering University of Waterloo WaterlooONN2L 3G1 Canada

ISBN: (纸本)9783540479222

Cluster analysis is an un-supervised learning technique that is widely used in the process of topic discovery from text. The research presented here proposes a novel un-supervised learning approach based on aggregation of clusterings produced by different clustering techniques. By examining and combining two different clusterings of a document collection, the aggregation aims at revealing a better structure of the data rather than imposing one that is imposed or constrained by the clustering method itself. When clusters of documents are formed, a process called topic extraction picks terms from the feature space (i.e. the vocabulary of the whole collection) to describe the topic of each cluster. It is proposed at this stage to re-compute terms weights according to the revealed cluster structure. The work further investigates the adaptive setup of the parameters required for the clustering and aggregation techniques. Finally, a topic accuracy measure is developed and used along with the F-measure to evaluate and compare the extracted topics and the clustering quality (respectively) before and after the aggregation. Experimental evaluation shows that the aggregation can successfully improve the clustering quality and the topic accuracy over individual clustering techniques. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Cluster analysis

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