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2014 7th International C Conference on Computer Science and Software Engineering, C3S2E 2014

作者： Liu, Li Lu, Shujing Lu, Yue Suen, Ching Y. Department of Computer Science and Technology East China Normal University Shanghai 200241 China ECNU-SRI Joint Lab. for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Group Shanghai 200062 China Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal QC H3G 1M8 Canada

ISBN: (纸本)9781450327121

Mail sorting machines play an important role in postal automation. In this paper, we give a brief overview of mail sorting machines in China Post from a pattern recognition point of view. OCR techniques such as postcode recognition and address recognition are essential for mail sorting machines, which are considered as class imbalance problems in our study. In addition to OCR that mainly focuses on the characters in the image, some image-level features are exploited for near-duplicate envelope image matching, which is helpful in tracking pieces of mail in the network environment. © 2014 ACM.

关键词： Image matching

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Decision Fusion in Cooperative Adaptive Systems

Decision Fusion in Cooperative Adaptive Systems

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The 8th International Conference on Computer Supported Cooperative Work in Design(第八届计算机支持的协同工作设计国际会议)(CSCWD2004)

作者： Mohamed Kamel Pattern Analysis and Machine Intelligence Lab.University of Waterloo Waterloo OntarioCanadaN2L 3G1

Research on cooperative, adaptive intelligentsystems, involves studying, developing and evaluatingarchitectures and methods to solve complex problemsusing adaptive and cooperative systems. These systemsmay range from simple software modules (such as aclustering or a classification algorithm) to physicalsystems (such as autonomous robots, machines orsensors).The main characteristic of these systems is that theyare adaptive and cooperative. By adaptive, it is meantthat the systems have a learning ability that makes themadjust their behaviour or performance to cope withchanging situations. The systems are willing tocooperate together to solve complex problems or toachieve common *** pattern recognition, there are notable contributionson the use of multiple classifiers. The most dominantdecomposition model used is an ensemble of classifiers(identical structures) that are trained differently. Mostof the innovations are in the combining methods. Thereare weighting and voting approaches, probabilisticapproaches and approximate and fuzzy logicapproaches. In the area of sensor fusion, there havebeen some interesting ideas for fusing the data anddecisions of the sensors. However, most of thesecombining schemes are usually applied as a postprocessing *** this work are concerned with investigatingarchitectures and methods of aggregating decisions in amulti-classifier or multi-agent environment. Newarchitectures that allow active cooperation will bedeveloped. The classifiers (or agents) have to knowsome knowledge about others in the system. Differentforms of cooperation will be reported. In order for thesearchitectures to allow for dynamic decision fusion, theaggregation procedures have to have the flexibility toadapt to changes in the input and output and adjust toimprove on the final output. Changes will be learned bymeans of extracting features using feature *** of these architectures to problems inclassification of data, distributed data mining a

关键词： Adaptive systems Intelligent sensors Sensor fusion Data mining Feature extraction Computer vision Intelligent systems Intelligent robots machine intelligence Computer architecture

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ART-based Clustering Aggregation

ART-based Clustering Aggregation

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IEEE International Conference on Granular Computing (GRC)

作者： Y. Yang M.S. Kamel F. Jin School of Information Science and Technology Southwest Jiaotong University Chengdu China Pattern Analysis and Machine Intelligence Lab the Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

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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 novel computational intelligence approach for multiple-point routing in communication networks

A novel computational intelligence approach for multiple-poi...

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IEEE International Conference on Systems, Man and Cybernetics

作者： S. Al-Sharhan F. Karray W. Gueaieb Department of Systems Design Engineering University of Waterloo Ontario Canada Pattern Analysis and Machine Intelligence (PAMI) Lab Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

A new evolutionary algorithm for the constrained multiple destination routing problem is presented. The constrained multicast problem is characterized by a minimum cost multicast tree and a bounded end-to-end delay. It has been proven that this problem is NP-complete. The proposed algorithm is based on a soft computing technique that integrates in an efficient manner the merits of genetic algorithms and concepts of the competitive learning in the artificial neural networks literature. A population based learning algorithm is utilized, among other techniques, to construct a delay bounded multicast tree. A salient feature of the algorithm is the adaptive learning concept that achieves an efficient trade-off between the exploration and exploitation of the search space.

关键词： Computational intelligence Routing Communication networks Multicast algorithms Delay Evolutionary computation Costs Computer networks Genetic algorithms Artificial neural networks

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Distributed nonlinear model predictive control and metric learning for heterogeneous vehicle platooning with cut-in/cut-out maneuvers

arXiv

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arXiv 2020年

作者： Basiri, Mohammad Hossein Ghojogh, Benyamin Azad, Nasser L. Fischmeister, Sebastian Karray, Fakhri Crowley, Mark The Department of Systems Design Engineering University of Waterloo ON Canada The Department of Electrical and Computer Engineering University of Waterloo ON Canada The Smart Hybrid and Electric Vehicles Systems Lab The Real-Time Embedded Software Lab The Machine Learning Lab The Centre for Pattern Analysis and Machine Intelligence

Vehicle platooning has been shown to be quite fruitful in the transportation industry to enhance fuel economy, road throughput, and driving comfort. Model Predictive Control (MPC) is widely used in literature for platoon control to achieve certain objectives, such as safely reducing the distance among consecutive vehicles while following the leader vehicle. In this paper, we propose a Distributed Nonlinear MPC (DNMPC), based upon an existing approach, to control a heterogeneous dynamic platoon with unidirectional topologies, handling possible cut-in/cut-out maneuvers. The introduced method addresses a collision-free driving experience while tracking the desired speed profile and maintaining a safe desired gap among the vehicles. The time of convergence in the dynamic platooning is derived based on the time of cut-in and/or cut-out maneuvers. In addition, we analyze the improvement level of driving comfort, fuel economy, and absolute and relative convergence of the method by using distributed metric learning and distributed optimization with Alternating Direction Method of Multipliers (ADMM). Simulation results on a dynamic platoon with cut-in and cut-out maneuvers and with different unidirectional topologies show the effectiveness of the introduced method. Copyright © 2020, The Authors. All rights reserved.

关键词： Topology

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Novel Global and Local Features for Near-Duplicate Document Image Matching

Novel Global and Local Features for Near-Duplicate Document ...

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International Conference on pattern Recognition

作者： Li Liu Yue Lu Ching Y. Suen Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal Canada Department of Computer Science and Technology East China Normal University Shanghai China Joint Lab for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Shanghai

ISBN: (纸本)9781479952106

A new near-duplicate document image matching approach is proposed. Globally, we model the spatial arrangements of objects in an image. Locally, the micro-patterns within each object are captured. To define a micro-pattern, the N-nary center-symmetric gray value differences in an image local neighborhood of a variable radius are exploited. A visual descriptor is proposed to characterize the appearance of the object based on micro-pattern distributions. By combining the global and local features, each document image is represented by a compact signature with a variable length. We employ Earth Mover's Distance for image dissimilarity computation, which stands out for its remarkable ability to tolerate the instability of object segmentation by allowing many-to-many correspondence among objects. Extensive experiments on two data sets demonstrate the effectiveness of the proposed approach.

关键词： Image matching Histograms Mercury (metals) Earth Object segmentation Sorting Databases

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Enhancement of vessel contours in retinal angiograms

Enhancement of vessel contours in retinal angiograms

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： N.M. Wanas M.R. El-Sakka M.S. Kamel Pattern Analysis and Machine Intelligence lab Department of Systems Design Engineerihg University of Waterloo Waterloo ONT Canada Department of Computer Science Faculty of Science University of Western Ontario London ONT Canada

Accurate and automatic assessment of angiograms has been sought as a powerful diagnostic tool in medical analysis, such as in diabetic retinopathy. These retinal angiogram images are characterized by poor local contrast. Applications of existing edge detection algorithms yield unsatisfactory results. In this paper, a set of cascaded linear directional filters is used to better enhance edges. Results show improvement in visual quality of the images.

关键词： Retina Image edge detection pattern analysis Diseases Blood vessels Biomedical imaging Image analysis Image segmentation machine intelligence System analysis and design

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URBAN LAND-COVER CLASSIFICATION FROM HIGH RESOLUTION REMOTE SENSING IMAGERY

URBAN LAND-COVER CLASSIFICATION FROM HIGH RESOLUTION REMOTE ...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Safaa M. Bedawi Mohamed N. Moustafa Mohamed S. Kamel National Authority for Remote Sensing and Space Sciences Cairo Egypt American University in Cairo Computer Science and Engineering Cairo Egypt Pattern analysis and Machine Intelligence Lab. university of Waterloo Waterloo Ontario Canada

ISBN: (纸本)9781479911127

In this paper, we consider an invariant Generalized Hough Transform (GHT) as a shape based extractor to improve the quality of the urban land-cover classification. Dense urban environment sensed by Very High-Resolution (VHR) optical sensors is one of the most challenging problems in pattern analysis and machine intelligence systems in remote sensing. We propose a three stage framework for extracting urban land-cover: a spectral cluster-based segmentation to segment and extract basic urban classes followed by two serialized classifications to extract structures of interest from the segmented data. The first classification uses Particle Swarm Optimization and shows a significant classification performance of 80-90% of roads of VHR remote sensing data over urban areas. Next, the classified data are piped into the third stage in which GHT is used to classify building areas. The suggested framework is successful in enhancing the building areas detection with an accuracy improvement of 30- 40%.

关键词： Land-cover Classification Particle Swarm Optimization Urban areas urban area Particle swarm optimization remote sensing land cover building area High definition images extraction device pattern analysis

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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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