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检索条件"机构=Pattern Analysis and Machine Intelligence LaboratoryDepartment of Systems Design Engineering"

共 68 条记录，以下是31-40 订阅

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

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

引用

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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Extraction of text phrases using hierarchical grammar 15th

Extraction of text phrases using hierarchical grammar

引用

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

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

ISBN: (纸本)9783540479222

This paper presents an algorithm for extraction of phrases from text *** e algorithm builds phrases by iteratively merging bigrams according to an association *** o association measures are presented: mutual information and t-test.T he extracted phrases are tested in a document classification task using a tf/idf model and a k-nearest neighbor classifier. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Extraction

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Image registration using virtual circles and edge direction

Image registration using virtual circles and edge direction

引用

16th International Conference on pattern Recognition, ICPR 2002

作者： Alhichri, Haikel Salem Kamel, Mohamed Systems Design Engineering Pattern Analysis and Machine Intelligence Lab University of Waterloo WaterlooONN2L3G1 Canada

ISBN: (纸本)0769516963

In this paper, we combine a novel set of image features called virtual circles with edge direction, to provide an efficient alignment algorithm for image registration under similarity transformations. Virtual circles can be extracted efficiently from many types of images with the kelp of the distance transform. They can also have extra information, such as their radius and the dominant edge direction in neighborhood, which can be used for efficient registration. A heuristic called the smoothness criterion is used to choose virtual circles which are less likely to be corrupted by background noise, and to increases the efficiency of the algorithm. Experimental results have shown that this method is highly automatic and has linear complexity in terms of the number of virtual circles extracted. © 2002 IEEE.

关键词： Image registration

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Image registration using virtual circles and edge direction

Image registration using virtual circles and edge direction

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作者： Alhichri, Haikel Salem Kamel, Mohamed Pattern Analysis and Machine Intelligence Lab. Systems Design Engineering University of Waterloo Waterloo Ont. N2L 3G1 Canada

In this paper, we combine a novel set of image features called virtual circles with edge direction, to provide an efficient alignment algorithm for image registration under similarity transformations. Virtual circles can be extracted efficiently from many types of images with the help of the distance transform. They can also have extra information, such as their radius and the dominant edge direction in neighborhood, which can be used for efficient registration. A heuristic called the smoothness criterion is used to choose virtual circles which are less likely to be corrupted by background noise, and to increases the efficiency of the algorithm. Experimental results have shown that this method is highly automatic and has linear complexity in terms of the number of virtual circles extracted. © 2002 IEEE.

关键词： Image segmentation

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Image registration using virtual circles and edge direction

Image registration using virtual circles and edge direction

引用

International Conference on pattern Recognition

作者： H.S. Alhichri M. Kamel Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada

In this paper we combine a novel set of image features called virtual circles with edge direction, to provide an efficient alignment algorithm for image registration under similarity transformations. Virtual circles can be extracted efficiently from many types of images with the help of the distance transform. They can also have extra information, such as their radius and the dominant edge direction in the neighborhood, which can be used for efficient registration. An heuristic called the smoothness criterion is used to choose virtual circles which are less likely to be corrupted by background noise, and to increases the efficiency of the algorithm. Experimental results have shown that this method is highly automatic and has linear complexity in terms of the number of virtual circles extracted.

关键词： Image registration Layout Data mining Switches pattern analysis machine intelligence System analysis and design design engineering systems engineering and theory Computer vision

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A coordination mechanism for model-based multi-sensor planning

A coordination mechanism for model-based multi-sensor planni...

引用

IEEE International Symposium on Intelligent Control (ISIC)

作者： M. Kamel L. Hodge Department of Systems Design Engineering Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Waterloo ONT Canada

This paper presents a multi-agent system for coordinating the deployment of multiple sensors in a modeled environment. The sensing task is the maximal sensor coverage of one or more targets in a scene and the position of each sensor is controlled by an autonomous agent. The agents rely on negotiation to achieve the level of coordination necessary to accomplish the given sensing task. Currently, the system focuses on the use of cameras for visual inspection tasks in which a single camera may be inadequate due to occluding objects in the scene, the number of targets to be observed or the sheer size of the target. The paper presents the negotiation mechanism developed for the multi-agent planning of the camera positions and illustrates its effectiveness by an example. Results show that the agents were able to autonomously position the cameras so as to allow for an acceptable level of coverage of the targets being observed.

关键词： Cameras Sensor systems Layout Inspection Intelligent sensors Sensor phenomena and characterization Control systems Art pattern analysis machine intelligence

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Weighted combination of neural network ensembles

Weighted combination of neural network ensembles

引用

International Joint Conference on Neural Networks (IJCNN)

作者： N.M. Wanas M.S. Kamel Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

There exist numerous schemes and methods to determine the output of an ensemble of classifiers. The most common approach being the majority vote. Furthermore, we might expect that an improvement can be achieved if there is a method by which we may weigh the members of the ensemble according to their individual performance. The feature based approach presented an architecture that tries to approach this target. However, if there is a way that the final classification may influence these weights we should expect an increased performance in the overall classification task. In this paper we present a new training algorithm that utilizes a feedback mechanism to iteratively improve the classification capability of the feature based approach. This approach is compared with the standard training method as well as standard aggregation schemes for combining classifier ensembles. Empirical results show that this architecture improved on classification accuracy.

关键词： Neural networks Voting Detectors pattern analysis machine intelligence System analysis and design design engineering systems engineering and theory Iterative algorithms Jacobian matrices

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Shape representation using concavity graphs

Shape representation using concavity graphs

引用

International Conference on pattern Recognition

作者： O. El Badawy M. Kamel Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada Systems Design Engineering University of Waterloo Waterloo ON Canada

In this paper, a new graph data structure for 2-D shape representation is proposed. The new structure is called a concavity graph, and is an evolution from the already known "concavity tree". Even though a concavity graph bears a fundamental resemblance to a concavity tree, the former is able to describe the shape of multiple objects in an image and their spatial configuration, and is hence inherently more complex. The aim of concavity graphs is two-fold: first we want to analyze the patterns in a multi-object image in a way that will (1) provide better representation of their shapes, and (2) convey useful information about how they "interact" together. Second, we want our analysis technique to facilitate similarity matching between two images. This paper introduces the new structure and outlines how it can be used for shape representation as well as similarity matching.

关键词： Shape Tree graphs Image analysis pattern analysis Data structures machine intelligence Laboratories System analysis and design design engineering systems engineering and theory

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Software architecture for real-time autonomous agents: a case study for digital train system

Software architecture for real-time autonomous agents: a cas...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： Insop Song F. Karray PAMI (Pattern Analysis Machine Intelligence) Group Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

In this paper, a software architecture for multiple autonomous agents in a real-time environment is described. The software architecture for autonomous agents must effectively connect perception modules, planning modules and action modules. It is necessary to define both an interface and a data flow among different modules. The proposed software architecture connects reactive modules with deliberative modules. The architecture proved its feasibility by controlling a prototype of multiple model digital trains.

关键词： Software architecture Real time systems Autonomous agents Computer aided software engineering Computer architecture Switches Mobile robots Communication system control Computer errors pattern analysis

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Shape representation using concavity graphs

Shape representation using concavity graphs

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作者： El Badawy, Ossama Kamel, Mohamed Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo 200 University Ave. W. Waterloo Ont. N2L 3G1 Canada

In this paper, a new graph data structure for 2-D shape representation is proposed. The new structure is called a concavity graph, and is an evolution from the already known "concavity tree". Even though a concavity graph bears a fundamental resemblance to a concavity tree, the former is able to describe the shape of multiple objects in an image and their spatial configuration, and is hence inherently more complex. The aim of concavity graphs is two-fold: first we want to analyze the patterns in a multi-object image in a way that will (1) provide better representation of their shapes, and (2) convey useful information about how they "interact" together. Second, we want our analysis technique to facilitate similarity matching behveen two images. This paper introduces the new structure and outlines how it can be used for shape representation as well as similarity matching. © 2002 IEEE.

关键词： pattern recognition

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