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International Joint Conference on Neural Networks (IJCNN)

作者： F. Sahba H.R. Tizhoosh M.M.A. Salama Pattern Analysis and Machine Intelligence Laboratory Department of System Design Engineering University of Waterloo Waterloo ONT Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

This paper introduces a new method to medical image segmentation using a reinforcement learning scheme. We use this novel idea as an effective way to optimally find the appropriate local thresholding and structuring element values and segment the prostate in ultrasound images. Reinforcement learning agent uses an ultrasound image and its manually segmented version and takes some actions (i.e., different thresholding and structuring element values) to change the environment (the quality of segmented image). The agent is provided with a scalar reinforcement signal determined objectively. The agent uses these objective reward/punishment to explore/exploit the solution space. The values obtained using this way can be used as valuable knowledge to fill a Q-matrix. The reinforcement learning agent can use this knowledge for similar ultrasound images as well. The results demonstrate high potential for applying reinforcement learning in the field of medical image segmentation.

关键词： Learning Biomedical imaging Image segmentation Ultrasonic imaging Medical diagnostic imaging pattern analysis machine intelligence Laboratories System analysis and design design engineering

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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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Digital compressor structure in neural network implementation using complex complementary pass-transistor logic (C/sup 2/PL)

Digital compressor structure in neural network implementatio...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： D. Zhang M. Kamel M.I. Elmasry VLSI Research Group Department of Electrical & Computer Engineering University of Waterloo Waterloo ONT Canada Pattern Analysis & Machine Intelligence Systems Design Engineering University of Waterloo Waterloo ONT Canada

In this paper, a compressor structure based on complex complementary pass-transistor logic (C/sup 2/PL) is presented. Some types of 3-2 compressors in C/sup 2/PL are achieved and a number of experiments are conducted to optimize their performance. Two typical compressor building blocks, the 4-2 compressor and 7-3 compressor, are built and their digital neural network (DNN) applications are discussed. Compared with the complementary pass-transistor logic (CDL) designs, our simulations show that the C/sup 2/PL compressor has the best performances in power, delay and number of transistors.

关键词： Intelligent networks Neural networks CMOS logic circuits Logic design Switches Semiconductor device modeling design engineering Neurons CMOS technology Voltage

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analysis and optimization of a non-time based motion controller for a nonholonomic mobile robot

Analysis and optimization of a non-time based motion control...

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IEEE International Symposium on Computational intelligence in Robotics and Automation (CIRA)

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

In this paper, a non-time based tracking controller of a nonholonomic mobile robot is first analyzed. Non-time based motion controllers have been successfully applied to many areas such as robot motion control, multi-robot coordination, force control, robotic teleoperation and manufacturing automation. However, by the traditional non-time based motion controller many suffer from oscillations in both the linear and angular velocities when there is a large initial tracking error. In this paper, a traditional non-time based tracking controller is optimized using a genetic algorithm, which is used to generate the model parameters that could guarantee the system stability and convergence of tracking error. Simulations using a nonholonomic mobile robot model with a four degree of freedom are conducted to investigate the performance of the proposed controller. The results using the proposed model is compared to those of the conventional model. Generally the proposed model performs better than the conventional model because the genetic algorithm can provide better parameters to minimize tracking error and the oscillation.

关键词： Motion analysis Motion control Mobile robots Automatic control Force control Error correction Genetic algorithms Robot motion Robot control Robot kinematics

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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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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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A branch-and-bound method for finding independently distributed probability models that satisfy probability order constraints

A branch-and-bound method for finding independently distribu...

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IEEE International Conference on systems, Man and Cybernetics

作者： B.K. Sy Xiao Ying Han Pattern Analysis and Machine Intelligence Group System Design Engineering Department University of Waterloo Waterloo ONT Canada Department of Computer Science CUNY Flushing NY USA

A branch-and-bound method for finding independently distributed probability models is presented. Such models attempt to capture expert preference by (inequality) order relationships and are useful for the development of decision support systems. Finding probability models with independent distributions can be formulated as a linear-constraint optimization problem with a dynamic cost function. A simplex-like algorithm was implemented for branching and bounding between two search spaces on finding the desired models. In these two search spaces, one encompasses all possible independent probability distributions, while the other encompasses all distributions that satisfy all probability order constraints.

关键词： Probability distribution Random variables Decision making Costs Mathematical model Educational institutions pattern analysis machine intelligence Computer science System analysis and design

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Cooperation: Concepts and General Typology

Cooperation: Concepts and General Typology

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IEEE International Conference on systems, Man and Cybernetics

作者： Alaa M. Khamis Mohamed S. Kamel Miguel A. Salichs Pattern Analysis and Machine Intelligence (PAMI) Laboratory University of Waterloo Canada RoboticsLab Department of Systems Engineering and Automation Carlos III Technical University of Madrid Spain PAMI Laboratory Electrical and Computer Engineering Department University of Waterloo Canada

Life on this planet is full of astonishing examples of cooperation. Individual species depend upon one another for sustenance, often forming surprising alliances to achieve a common goal: continuance of the species. The majority of living things also display amazing altruism in order to protect and provide the best care for their offspring, incomparable to any form of sacrifice shown by human beings. Studying the cooperation patterns between living things and their intelligent behaviors has been source of inspiration for many new algorithms, theories and systems. This paper addresses the concept of cooperation and why it is important. It highlights the available biologically-inspired models and algorithms, and their potential applications. The paper also presents a general typology of cooperation patterns, which can help to understand how systems could work cooperatively in an intelligent manner.

关键词： Intelligent systems Biological system modeling Intelligent robots Artificial intelligence Cybernetics Planets Displays Protection Humans Multiagent systems

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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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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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