California Institute of Technology, Editorial BoardNonlinear Analysis: Hybrid Systems, 2016-presentIEEE CSS Conference Editorial Board, 2018-presentJournal of Nonlinear Systems and Applications, 2015-2016, Program/Technical CommitteeACM International Conference on Hybrid Systems: Computation and Control, 2016, 2017, 2018, 2019IFAC Conference on Analysis and Design of Hybrid Systems, 2018, 2021IEEE CSS Technical Committee on Computational Aspects of Control System Design, 2017-presentIEEE CSS Technical Committee on Hybrid Systems, 2014–present, MemberCanadian Applied and Industrial Mathematics Society (CAIMS)IEEE Control Systems Society (CSS)Institute of Electrical and Electronics Engineers (IEEE)Society for Industrial and Applied Mathematics (SIAM), Reviewer Energy management strategy (EMS) is playing a key role to improve the energy efficiency of this CPS.
2405-2418, June, 2012. This paper presents a novel bidirectional long shortterm memory (LSTM) network based parallel reinforcement learning (PRL) approach to construct EMS for a hybrid tracked vehicle (HTV). He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory.
MC 6108
Institution: University of Waterloo.
482 - 496, 2015. Overview. Liu, L., P. Fieguth, G. Zhao, and M. Pietikäinen, "Extended Local Binary Pattern Fusion for Face Recognition",International Conference on Image Processing, 2014. Short biography Ying Liu received her Ph.D. degree in the field of signal and image processing at the University of Waterloo in the department of Systems Design Engineering in 2011.
www.itsslab.com. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Details, Liu, L., P. Fieguth, L. Zhao, Y. degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. His main research interests are in the theory and applications of hybrid systems and control, including rigorous computational methods for control design with applications in robotics and cyber-physical systems.
Xixia Liu, Rong Wu, Jimmy Huang, Fang Xu (not in picture: Mohamad Zandieh, Shuxia Xu, Yongjie Yang, Junling Duan) October 5, 2018 Jennifer Moon, Yawen Wang, Dai Li, Yanping He
First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included.
University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services.
Then the proposed deep reinforcement learning control system is trained and verified by the realistic driving condition with high-precision, and is compared with the benchmark method DP and the traditional DQL method. 519-888-4567 x37550
She received her B.E.
Acs Nano2011; 5: 1304–12. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Lab.
This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab.
2, pp. Department of Civil and Environmental Engineering at University of Waterloo.
Intelligent energy management of hybrid electric vehicles
Canada Research Chair and Assistant Professor. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S.
Overview.
Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV. Liu, L., B. Yang, P. Fieguth, Z. Yang, and Y. Wei, "BRINT: A Binary Rotation Invariant and Noise Tolerant Texture Descriptor", International Conference on Image Processing, Melbourne, 2013. May 2017, Dr. Liu attended the ICAS 2017 conference (International Congress on Analytical Sciences) at Haikou, China, and received a youth presentation award. Then, the synthesized data from this parallel system is trained by a bidirectional LSTM network. Details Visit our COVID-19 information website to learn how Warriors protect Warriors. Finally, the deep Q-network is applied to derive the intelligent driving policies for the ego vehicle.
Jun Liu received the B.S.
Liu, L., Y. Wei, P. Fieguth, and G. Kuang, "Fusing Sorted Random Projections for Robust Texture Classification and Material Categorization", IEEE Transactions on Circuits and Systems for Video Technology, vol. 86-99, 2012.
25, no. Home; Research; Publications; Members; Teaching; CV; Group News; Opening; Funding; Chemistry; Nanotech; Links This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment. Finally, the control performance of the derived DM policies in safety and efficiency is analyzed. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. Long, P. Fieguth, S. Lao, and G. Zhao, "BRINT: Binary Rotation Invariant and Noise Tolerant Texture Classification", IEEE Transactions on Image Processing, vol.
My current researches are both in biomedical imaging and remote sensing. 30, no. Most Liked Posts [2ND CCWT] Call for Abstracts; Our Safety-Related Research was Featured on the Media! +1 519 888 4567, ext. 23, no. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). December 26, 2016, Feng's paper on liposome/nanoparticle interaction on Angew. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. Department: Department of Mechanical and Mechatronics Engineering.
Feb 2014, Dr. Liu won the Fred Beamish Award. One of our papers was included in a Virtual Issue of Langmuir, which includes some of the most important papers in the history of the journal.
6, pp. First, the highway DM problem is formulated, wherein the vehicles can exchange information via wireless networking. This work proposes a deep reinforcement learning (DRL) based left-turn decision-making framework at unsignalized intersection for autonomous vehicles. Dave N, Liu J. 7, 2014. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. During her PhD study she spent two years as a Visiting Student at the University of Waterloo, Canada, and she has held a visiting appointment at the Peking University in China. Liu, L., P. Fieguth, and G. Kuang, "Generalized Local Binary Patterns for Texture Classification", British Machine Vision Conference, Dundee, 2011.
Our active work toward reconciliation takes place across our campuses through research, learning, teaching, and community building, and is centralized within our Indigenous Initiatives Office. Supervisors Paul Fieguth Research interests I'm interested in the fields of image processing, computer vision, pattern recognition and related areas. Mater.2011; in press.
Congratulations to Dr. Tae J. Kwon! Decision-making module enables autonomous vehicles to reach appropriate maneuvers in the complex urban environments, especially the intersection situations. December 26, 2016, Feng's paper on liposome/nanoparticle interaction on Angew. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. 45, no.
7. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. Details.
Visit our COVID-19 information website to learn how Warriors protect Warriors. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. Her current research interests include computer vision, texture analysis, pattern recognition and image processing. Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. Dave N, Liu J. Please contact Dr. Liu for research opportunities. j.liu@uwaterloo.ca. Numerous journals and conferences, some book publishers, and several funding agencies. Department of Mechanical and Mechatronics Engineering, Decision-making at Unsignalized Intersection for Autonomous Vehicles: Left-turn Maneuver with Deep Reinforcement Learning, Reinforcement Learning-Enabled Decision-Making Strategies for a Vehicle-Cyber-Physical-System in Connected Environment, Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study, Deep reinforcement learning based energy management for a hybrid electric vehicle, Parallel reinforcement learning-based energy efficiency improvement for a cyber-physical system, instructions how to enable JavaScript in your web browser, Decision-making of autonomous vehicles
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