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Canadian Conference on Computer and Robot Vision, CRV

作者： M. Shokri H.R. Tizhoosh Pattern Analysis and Machine Intelligence Lab Systems Design Engineering University of Waterloo ONT Canada

One of the problems in image processing is finding an appropriate threshold in order to convert an image to a binary one. In this paper we introduce a new method for image thresholding. We use reinforcement learning as an effective way to find the optimal threshold. Q(Λ) is implemented as a learning algorithm to achieve more accurate results. The reinforcement agent uses objective rewards to explore/exploit the solution space. It means that there is not any experienced operator involved and the reward and punishment function must be defined for the agent. The results show that this method works successfully and can be trained for any particular application.

关键词： Learning Histograms Image processing Image converters Image segmentation pattern analysis machine intelligence System analysis and design design engineering systems engineering and theory

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Shape retrieval using concavity trees

Shape retrieval using concavity trees

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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

Concavity trees are well-known abstract structures. This paper proposes a new shape-based image retrieval method based on concavity trees. The proposed method has two main components. The first is an efficient (in terms of space and time) contour-based concavity tree extraction algorithm. The second component is a recursive concavity-tree matching algorithm that returns a distance between two trees. We demonstrate that concavity trees are able to boost the retrieval performance of two feature sets by at least 15% when tested on a database of 625 silhouette images.

关键词： Shape Image retrieval Information retrieval Testing Image databases pattern recognition pattern analysis machine intelligence Laboratories System analysis and design

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A fuzzy set approach to extracting keywords from abstracts

A fuzzy set approach to extracting keywords from abstracts

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： M. Makrehchi M. Kamel Pattern Analysis and Machine Intelligence Lab Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada Department of Systems Design Engineering University of Waterloo Waterloo Ontario Canada

An unsupervised keyword extraction method based on corpora is proposed. After representing each document in the collection by a fuzzy set of candidate keywords, the problem is translated into finding appropriate fuzzy membership degree for each candidate. In order to determine the membership degrees, first, all terms of the vocabulary are mapped into a two-dimensional space called class-collection map by obtaining two newly proposed fuzzy measures called fuzzy significance and fuzzy relevance for each term. At the second step, the mapped terms are grouped into three categories, namely, features, keywords and stopwords that are discriminated by their contribution to the meaning of the documents. Instead of a clustering approach for grouping purpose, a fuzzy rule base is provided. The method is independent of the language and data dimensionality. It does not require the use of dictionary, thesaurus nor natural language processing.

关键词： Fuzzy sets Vocabulary Web pages Abstracts Text mining Fuzzy systems pattern analysis machine intelligence System analysis and design design engineering

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A reinfrocement learning approach to online learning in control

A reinfrocement learning approach to online learning in cont...

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Fourth International Conference on Control and Automation

作者： Tehrani, Ali M. Kamel, Mohamed S. Pattern Analysis and Machine Intelligence Lab Systems Design Engineering Department University of Waterloo Waterloo Ont. N2L 3G1 Canada

ISBN: (纸本)078037777X

In search for a reinforcement learning technique with the simplicity of tabular techniques and capability of dealing with continuous states like in fuzzy systems, we introduce a new approach, which we have called Adaptive Pseudo Fuzzy technique. The idea is to partition the state space with some window functions similar to fuzzy membership functions and learn the output values by changing the rules' consequents directly. This is a kind of local function approximation similar to RBFs and CMACs , however, unlike RBFs it does not shift the basis, and unlike CMACs it does not go through complex coarse coding. This method represents the input as a fuzzy system and learns the output as a look-up-table. We employed this technique in Sarsa(λ) to build a general online controller and examined it for a pole-balancing problem. © 2003 IEEE.

关键词： Learning systems

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Data dependence in combining classifiers

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4th International Workshop on Multiple Classifier systems, MCS 2003

作者： Kamel, Mohamed S. Wanas, Nayer M. Pattern Analysis and Machine Intelligence lab Department of Systems Design Engineering University of Waterloo WaterlooONN2L-3G1 Canada

ISBN: (纸本)3540403698

It has been accepted that multiple classifier systems provide a platform for not only performance improvement, but more efficient and robust pattern classification systems. A variety of combining methods have been proposed in the literature and some work has focused on comparing and categorizing these approaches. In this paper we present a new categorization of these combining schemes based on their dependence on the data patterns being classified. Combining methods can be totally independent from the data, or they can be implicitly or explicitly dependent on the data. It is argued that data dependent, and especially explicitly data dependent, approaches represent the highest potential for improved performance. On the basis of this categorization, an architecture for explicit data dependent combining methods is discussed. Experimental results to illustrate the comparative performance of some combining methods according to this categorization is included. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Computers

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A Reinfrocement Learning Approach to Online Learning in Control

A Reinfrocement Learning Approach to Online Learning in Cont...

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International Conference on Control and Automation (ICCA)

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

In search for a reinforcement learning technique with the simplicity of tabular techniques and capability of dealing with continuous states like in fuzzy systems, we introduce a new approach, which we have called Adaptive Pseudo Fuzzy technique. The idea is to partition the state space with some window functions similar to fuzzy membership functions and learn the output values by changing the rules’ consequents directly. This is a kind of local function approximation similar to RBFs and CMACs, however, unlike RBFs it does not shift the basis, and unlike CMACs it does not go through complex coarse coding. This method represents the input as a fuzzy system and learns the output as a look-up-table. We employed this technique in Sarsa(λ) to build a general online controller and examined it for a pole-balancing problem.

关键词： Fuzzy systems Learning State-space methods Function approximation

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RBF-based real-time hierarchical intrusion detection systems

RBF-based real-time hierarchical intrusion detection systems

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International Joint Conference on Neural Networks (IJCNN)

作者： Ju Jiang Chunlin Zhang M. Kamel Pattern Analysis and Machine Intelligence Research Group Systems Design Department Engineering Faculty University of Waterloo Canada Systems Design Department University of Waterloo Canada

An intrusion detection system (IDS) is an art to detect network intrusions by monitoring the network traffic patterns. Generally, an IDS uses only a single-layer detection structure; therefore it cannot adjust its structure adaptively and automatically. In this paper, two hierarchical IDSs, the serial hierarchical and parallel hierarchical IDSs, are proposed. Both of them are based on radial basis function (RBF) neural networks. Because of the short training time and high accuracy of the RBF neural networks, two hierarchical IDSs can monitor network traffic in real-time, train new classifiers for novel intrusions automatically, and modify their structures adaptively after new classifiers are trained.

关键词： Real time systems Intrusion detection Neural networks Telecommunication traffic Computerized monitoring Computer networks Condition monitoring pattern analysis machine intelligence System analysis and design

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Optimization of a Neural Dynamics Based Controller for a Nonholonomic Mobile Robot Using Genetic Algorithms

Optimization of a Neural Dynamics Based Controller for a Non...

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International Conference on Control and Automation (ICCA)

作者： Hao Li S.X. Yang F. Karray Pattern Analysis and Machine Intelligence (PAMI) Lab Systems Design Engineering University of Waterloo Waterloo ONT Canada Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

In this paper, a neural dynamics based controller for a nonholonomic mobile robot is proposed. The turn angle of the robot in the proposed model is characterized by a biologically inspired shunting equation derived from Hodgkin and Huxley’s membrane equation. This model is capable of generating smooth steering velocity command that drives the robot to track desired paths. Some parameters in the proposed neural dynamics based controller need to be selected. A genetic algorithm is designed to optimize the model parameters that can guarantee the convergence of tracking error of the mobile robot. Simulation studies of a fourdegree-of-freedom mobile robot are conducted, which demonstrate the effectiveness of the proposed motion controller.

关键词： Mobile robots Genetic algorithms Biological system modeling Equations Biomembranes Algorithm design and analysis design optimization Convergence Motion control

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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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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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