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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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A sensor model registration technique for mobile robot localization

A sensor model registration technique for mobile robot local...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： S.Y.T. Lang A.K.C. Wong Autonomous Systems Laboratory Institute of In formation Technology National Research Council Canada Ottawa ONT Canada Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

A method for mobile robot localization using natural environmental features is presented. An attributed graph boundary representation of free space is used. A local sensor model is registered with a global model by a subgraph isomorphism technique. Geometric and structural knowledge is used to search for mappings. The set of possible mappings is incrementally determined. Simultaneously, the associated coordinate transformation between the global and local models is refined. The model registration technique is implemented in software, and two examples are shown.< >

关键词： Mobile robots Sensor phenomena and characterization Dead reckoning Sonar navigation Councils Wires Laboratories Information technology Space technology Calibration

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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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AN ADAPTIVE APPROACH TO FEATURE SELECTION IN pattern RECOGNITION

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International Journal of pattern Recognition and Artificial intelligence 1990年第4期4卷 573-601页

作者： H.C. SHEN R. PILKEY Department of Systems Design Engineering Pattern Analysis and Machine Intelligence Group University of Waterloo Waterloo Ontario canada N2L 3G1 Canada Present address: Carma Industries 494 The Parkway Peterborough Ontario Canada K9J 7L9.

Feature selection is an important phase in most pattern recognition problems, especially when the space of the extracted features is very large. Feature selection methods attempt to reduce the feature space to satisfy certain objectives. We propose the concept of defining a performance potential as a measure of the effectiveness of the set of selected features. This paper begins by outlining a ranking scheme for features based on a feature’s calculated “performance potential”. The performance potential is made up of a number of performance measures: extraction time, memory requirements, variance, covariance and classification success. An adaptive scheme is proposed to process a number of initial features and arrive at the “best” subset based on their performance potential. The approach is applied to a texture analysis problem. The results of the testing of the approach point to conclusions concerning its effectiveness.

关键词： Feature selection pattern recognition Adaptive approach Performance potential

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A rough set approach for planner evaluation

A rough set approach for planner evaluation

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IEEE International Conference on systems, Man and Cybernetics

作者： B.K. Sy Wang Jiaxin Pattern Analysis and Machine Intelligence Group System Design Engineering Department University of Waterloo Waterloo ONT Canada Department of Computer Science CUNY Flushing NY USA The State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing China

This paper discusses a rough set approach for evaluating solutions of scheduling problems. Algorithms for solving scheduling problems are planners and the scheduling problems are modelled as constraint satisfaction problems. Conventional approach for the analysis of algorithms often focuses on the time and representational complexities, and assumes an identical cost on all operations. The proposed rough set approach augments conventional approaches for the analysis of algorithms in two ways: 1) it permits the consideration of different costs arising from different operations; and 2) it allows one to define a new utility for a complexity analysis.

关键词： Algorithm design and analysis Processor scheduling Set theory machine intelligence Computer science Costs Search problems Educational institutions pattern analysis System analysis and design

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Improving Vehicle Positioning and Visual Feature Estimates through Mutual Constraint

Improving Vehicle Positioning and Visual Feature Estimates t...

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International Conference on Intelligent Transportation

作者： Andrew Rae Otman Basir Pattern Analysis and Machine Intelligence (PAMI) Research Group Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

An argument is presented that a two-way relationship between position and visual information can be utilized to improve estimates of vehicle position as well as the interpretation of the surrounding environment. Simulation results for a formulation based on dynamic Bayesian networks illustrate that the belief in vehicle position is influenced by the measured visual features, while the belief in the value of said visual features is in turn influenced by GPS measurements of vehicle position. The weight of these influences, as well as the uncertainty of the resulting state estimates, depends directly upon the rate-of-change of the observed features. This information sharing approach represents a successful integration of these two technologies that leads to more plausible vehicle positioning and visual feature estimation that will be useful for purposes of automated driving and navigation systems.

关键词： Global Positioning System Position measurement Vehicle driving Intelligent vehicles Intelligent transportation systems Satellite navigation systems Shape measurement USA Councils Vehicle dynamics Bayesian methods

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A segmentation criterion for digital image compression

A segmentation criterion for digital image compression

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M.R. El-Sakka M.S. Kamel Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering Department University of Waterloo Waterloo ONT Canada University of Waterloo Waterloo ON CA Dept. of Syst. Design Eng. Waterloo Univ. Ont. Canada

This paper is concerned with segmenting light intensity images for the sake of compressing them using lossy compression techniques. Among the most commonly used techniques for image segmentation is quad-tree partitioning. In this technique, block variance based criteria are usually used to measure the smoothness of the segmented blocks and to consequently classify them. Block variance, however, does not consider the pixel value distribution within the block. Instead of using the block variance as a segmentation and classification measure, we propose using the mean squared deviation from the neighboring pixels mean. The proposed measure is capable of differentiating between blocks not only according to block pixel values but also according to their distribution within the block. This leads to a much better image segmentation and consequently to higher image compression ratios with lower image degradation. The results show the superiority of the proposed measure over the block variance measure.

关键词： Image segmentation Digital images Image coding Degradation

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Particle filtering for bearing-only audio-visual speaker detection and tracking

Particle filtering for bearing-only audio-visual speaker det...

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International Conference on Signals, Circuits and systems, SCS

作者： Andrew Rae Alaa Khamis Otman Basir Mohamed Kamel Pattern Analysis and Machine Intelligence (PAMI) research group Department of Electrical and Computer Engineering University of Waterloo Canada Department of Electrical and Computer Engineering University of Waterloo Canada PAMI research group Department of Electrical and Computer Engineering University of Waterloo Canada

ISBN: (纸本)9781424443970;9781424443987

We present a method for audio-visual speaker detection and tracking in a smart meeting room environment based on bearing measurements and particle filtering. Bearing measurements are determined using the Time Difference of Arrival (TDOA) of the acoustic signal reaching a pair of microphones, and by tracking facial regions in images from monocular cameras. A particle filter is used to sample the space of possible speaker locations within the meeting room, and to fuse the bearing measurements from auditory and visual sources. The proposed system was tested in a video messaging scenario, using a single participant seated in front of a screen to which a camera and microphone pair are attached. The experimental results show that the accuracy of speaker tracking using bearing measurements is related to the location of the speaker relative to the locations of the camera and microphones, which can be quantified using a parameter known as Dilution of Precision.

关键词： Filtering Particle tracking Loudspeakers Acoustic measurements Microphones Cameras Acoustic signal detection Particle measurements Time measurement Time difference of arrival

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A hierarchical genetic algorithm for the design of beta basis function neural network

A hierarchical genetic algorithm for the design of beta basi...

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International Joint Conference on Neural Networks (IJCNN)

作者： C. Aouiti A.M. Alimi F. Karray A. Maalej Faculty of Sciences of Bizerta Universite de Carthage Tunisia Department of Electrical Engineering REGIM: Research Group on Intelligent Machines University of Sfax Sfax Tunisia Systems design Engineering Department Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Waterloo ONT Canada Department of Mechanical Engineering University of Sfax ENIS Sfax Tunisia

We propose an evolutionary neural network-training algorithm for beta basis function neural networks (BBFNN). Classic training algorithms for neural networks start with a predetermined network structure. Generally the network resulting from learning applied to a predetermined architecture is either insufficient or over-complicated. This paper describes a hierarchical genetic learning model of the BBFNN. In order to examine the performance of the proposed algorithm, they were used for the approximation problems. The results obtained are very satisfactory with respect to the relative error.

关键词： Genetic algorithms Algorithm design and analysis Neural networks Artificial neural networks Biological cells Neurons Chaos machine intelligence Laboratories Convergence

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Search Space analysis of Recurrent Spiking and Continuous-time Neural Networks

Search Space Analysis of Recurrent Spiking and Continuous-ti...

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International Joint Conference on Neural Networks (IJCNN)

作者： M. Ventresca B. Ombuki Systems Design Engineering and member of the Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Waterloo ONT Canada Department of Computing and Information Science University of Guelph Guelph ONT Canada Computer Science Department Brock University Saint Catharines ONT Canada

The problem of designing recurrent continuous-time and spiking neural networks is NP-Hard. A common practice is to utilize stochastic searches, such as evolutionary algorithms, to automatically construct acceptable networks. The outcome of the stochastic search is related to its ability to navigate the search space of neural networks and discover those of high quality. In this paper we investigate the search space associated with designing the above recurrent neural networks in order to differentiate which network should be easier to automatically design via a stochastic search. Our investigation utilizes two popular dynamic systems problems; (1) the Henon map and (2) the inverted pendulum as a benchmark.

关键词： Neural networks Recurrent neural networks Stochastic processes Chaotic communication Neurons Biological system modeling Evolutionary computation Navigation Helium Visualization

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