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2nd International Conference on Advances in pattern Recognition, ICAPR 2001

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

ISBN: (纸本)3540417672

In this paper we present a new architecture for combining classifiers. This approach integrates learning into the voting scheme used to aggregate individual classifiers decisions. This overcomes the drawbacks of having static voting techniques. The focus of this work is to make the decision fusion a more adaptive process. This approach makes use of feature detectors responsible for gathering information about the input to perform adaptive decision aggregation. Test results show improvement in the overall classification rates over any individual classifier, as well as different static classifier-combining schemes. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Network architecture

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Application of reinforcement learning for segmentation of transrectal ultrasound images

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BMC Medical Imaging 2008年第1期8卷 1-10页

作者： Sahba, Farhang Tizhoosh, Hamid R. Salama, Magdy M.A. Medical Instrument Analysis and Machine Intelligence Group University of Waterloo Waterloo ON Canada Department of Systems Design Engineering University of Waterloo Waterloo ON Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada

Background: Among different medical image modalities, ultrasound imaging has a very widespread clinical use. But, due to some factors, such as poor image contrast, noise and missing or diffuse boundaries, the ultrasound images are inherently difficult to segment. An important application is estimation of the location and volume of the prostate in transrectal ultrasound (TRUS) images. For this purpose, manual segmentation is a tedious and time consuming procedure. Methods: We introduce a new method for the segmentation of the prostate in transrectal ultrasound images, using a reinforcement learning scheme. This algorithm is used to find the appropriate local values for sub-images and to extract the prostate. It contains an offline stage, where the reinforcement learning agent uses some images and manually segmented versions of these images to learn from. The reinforcement agent is provided with reward/punishment, determined objectively to explore/exploit the solution space. After this stage, the agent has acquired knowledge stored in the Q-matrix. The agent can then use this knowledge for new input images to extract a coarse version of the prostate. Results: We have carried out experiments to segment TRUS images. The results demonstrate the potential of this approach in the field of medical image segmentation. Conclusion: By using the proposed method, we can find the appropriate local values and segment the prostate. This approach can be used for segmentation tasks containing one object of interest. To improve this prototype, more investigations are needed. © 2008 Sahba et al;licensee BioMed Central Ltd.

关键词： Reinforcement Learning Processing Task TRUS Image Segmentation Approach Online Mode

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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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Representing uncertainty in robot task planning

Representing uncertainty in robot task planning

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IEEE International Conference on Robotics and Automation (ICRA)

作者： M.S. Kamel P.M. Kaufmann Pattern Analysis and Machine Intelligence Group Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

A representation for uncertain states within the context of robot task planning is described. This includes the probabilistic description of objects, relationships between objects, and operators. It is one component of a task planner designed for use in uncertain task domains. The planner is based on a game theoretic-approach which views the environment as an opponent (often fallible). Multiple outcomes arising from operator application in an uncertain world are attributed to moves of the opponent. These are called reaction operators. Their representation and effect on the planning process are discussed.< >

关键词： Uncertainty Robot sensing systems Process planning pattern analysis machine intelligence System analysis and design design engineering systems engineering and theory Intelligent robots Game theory

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Intelligent Database Query Translation

Intelligent Database Query Translation

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IEEE International Conference on systems, Man and Cybernetics

作者： M.S. Kamel W.S. Loo A.K.C. Wong Pattern Analysis and Machine Intelligence Group Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

In this paper we are concerned with techniques for processing database queries that are not required to be formulated based on complete and precise knowledge of the query specification as defined in the database management system. In specific, we consider processing queries that are ill-defined, not complete and fuzzy . We propose a query translator that tries to bridge the gap between the user's semantically stated query and its full specification as required by the database. The translator utilizes a graph based structure to represent queries and relations in the database. The translation process involves transforming incomplete query graphs into complete query graphs using attribute covering where the entities of the query are mapped to real entities of the database and functional dependency resolution, where the relational joins between these entities are established. The proposed translator is an attempt at incorporating intelligence in query processing systems to support user- friendly features such as cooperative and corrective responses from database systems.

关键词： Deductive databases Cities and towns Algebra Natural languages Topology Database languages Query processing

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Opposition-based Q(λ) algorithm

Opposition-based Q(λ) algorithm

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International Joint Conference on Neural Networks 2006, IJCNN '06

作者： Shokri, Maryam Tizhoosh, Hamid R. Kamel, Mohamed Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo 200 University Avenue West ON N2L 3G1 Canada Pattern Analysis and Machine Intelligence Laboratory Department of Electrical and Computer Engineering University of Waterloo 200 University Avenue West ON N2L 3G1 Canada

ISBN: (纸本)0780394909

The problem of delayed reward in reinforcement learning is usually tackled by implementing the mechanism of eligibility traces. In this paper we introduce an extension of eligibility traces to solve one of the challenging problems in reinforcement learning. The concept of opposition traces is proposed in this work to deal with large state space problems in reinforcement learning applications. We combine the idea of opposition and eligibility traces to construct the oppositionbased Q(λ). The results are compared with the conventional Watkins' Q(λ) and reflect a remarkable performance increase. © 2006 IEEE.

关键词： Reinforcement learning

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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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EVOL: ensembles voting online

EVOL: ensembles voting online

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International Joint Conference on Neural Networks (IJCNN)

作者： G. Auda M. Kamel Pattern Analysis And Machine Intelligence Lab Systems Design Engineering Department University of Waterloo Canada

Cooperation by voting is one of the popular modular neural network decision-making strategies. Ensemble classifiers are multiple identical modules which use voting for post-learning classification. This paper suggests a new cooperation scheme for ensembles which utilizes voting in the learning process itself. According to the suggested scheme, different modules would, automatically, focus on different regions in the input space. Hence, temporal crosstalk decreases and decision boundaries are drawn accurately in complex overlapping regions of the input space.

关键词： Voting Neural networks Decision making Multi-layer neural network Filtering Crosstalk pattern analysis machine intelligence System analysis and design design engineering

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Modular-Based Classifier for Phoneme Recognition

Modular-Based Classifier for Phoneme Recognition

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IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Abbas Ahmadi Fakhri Karray Mohamed Kamel Systems Design Engineering Department Pattern Analysis and Machine Intelligence Laboratory Waterloo ONT Canada Electrical and Computer Engineering Department Pattern Analysis and Machine Intelligence Laboratory Waterloo ONT Canada

This paper proposes a modular-based classifier for the problem of phoneme recognition. This is carried out by the use of a two-level classification approach including, high and low levels. We propose a new concept called phoneme family. To obtain phoneme families, we employ k-mean clustering method. A given unknown phoneme is first classified into a phoneme family at high level classification. Then, the exact label of the phoneme is determined at low level classification. We have used a combined framework of statistical and neural network based classifiers. Encouraging results are obtained by applying the proposed method on TIMIT database and its performance is compared against other methods

关键词： Neural networks Speech recognition Recurrent neural networks pattern recognition design engineering Databases Network topology Signal processing Information technology pattern analysis

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