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检索条件"机构=Intelligent Robotics and Computer Vision Group/Department of Computer Science and Mathematics"
293 条 记 录,以下是211-220 订阅
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F2A2: flexible fully-decentralized approximate actor-critic for cooperative multi-agent reinforcement learning
The Journal of Machine Learning Research
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The Journal of Machine Learning Research 2023年 第1期24卷 8447-8521页
作者: Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan Hongyuan Zha School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Software Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Computer Science and Technology Key Laboratory of Mathematics and Engineering Applications Ministry of Education East China Normal University Shanghai China Department of Computer Science and Engineering Key Laboratory of Artificial Intelligence Ministry of Education Shanghai Jiao Tong University Shanghai China
Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications due to non-interactivity between agents, the curse of dimensionality, and computation ... 详细信息
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Constrained Generative Sampling of 6-DoF Grasps
Constrained Generative Sampling of 6-DoF Grasps
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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)
作者: Jens Lundell Francesco Verdoja Tran Nguyen Le Arsalan Mousavian Dieter Fox Ville Kyrki KTH Royal Institute of Technology Sweden Department of Electrical Engineering and Automation Intelligent Robotics Group School of Electrical Engineering Aalto University Finland NVIDIA Corporation USA Paul G. Allen School of Computer Science & Engineering University of Washington Seattle USA
Most state-of-the-art data-driven grasp sampling methods propose stable and collision-free grasps uniformly on the target object. For bin-picking, executing any of those reachable grasps is sufficient. However, for co...
来源: 评论
Motion planning for a vigilant humanoid robot
Motion planning for a vigilant humanoid robot
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IEEE-RAS International Conference on Humanoid Robots
作者: Jean-Bernard Hayet Claudia Esteves Gustavo Arechavaleta Eiichi Yoshida Computer Science Group Centro de Investigación en Matemáticas Guanajuato Mexico Department of Mathematics Universidad de Guanajuato Guanajuato Mexico Robotics and Advance Manufacturing Group Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV) Saltillo Coahuila Mexico Intelligent Systems Research Institute National Institute for Advanced Industrial Science and Technology Tsukuba Ibaraki Japan
This paper presents a motion planner for a vigilant humanoid robot. In this context of surveillance, the robot task is to keep a distinctive point in the environment in sight during all of its motion. The method we pr... 详细信息
来源: 评论
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport
arXiv
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arXiv 2023年
作者: Bouniot, Quentin Redko, Ievgen Mallasto, Anton Laclau, Charlotte Arndt, Karol Struckmeier, Oliver Heinonen, Markus Kyrki, Ville Kaski, Samuel LTCI Télécom Paris Institut Polytechnique de Paris France Noah’s Ark Lab Paris France Smartly.io Finland Aalto University Finland Intelligent Robotics Group Finland Department of Computer Science University of Manchester United Kingdom
In the last decade, we have witnessed the introduction of several novel deep neural network (DNN) architectures exhibiting ever-increasing performance across diverse tasks. Explaining the upward trend of their perform... 详细信息
来源: 评论
A Review of Generalized Zero-Shot Learning Methods
arXiv
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arXiv 2020年
作者: Pourpanah, Farhad Abdar, Moloud Luo, Yuxuan Zhou, Xinlei Wang, Ran Lim, Chee Peng Wang, Xi-Zhao Jonathan Wu, Q.M. The Centre for Computer Vision and Deep Learning Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada Deakin University Australia The Department of Computer Science City University of Hong Kong Hong Kong The College of Mathematics and Statistics Shenzhen Key Lab. of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China The College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China
Generalized zero-shot learning (GZSL) aims to train a model for classifying data samples under the condition that some output classes are unknown during supervised learning. To address this challenging task, GZSL leve... 详细信息
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Industrial machine vision: lessons and challenges
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Optics News 1987年 第2期13卷 12-17页
作者: Steven W. Holland Robert B. Tilove STEVEN W. HOLLAND is an assistant department head in the Computer Science Dept. of General Motors Research Laboratories (GMR). He is responsible for research projects involving computer vision robotics mobile robotics process planning knowledge systems natural language advanced programming environments parallel processing and statistics. ROBERT B. TILOVE is senior staff research scientist and project leader of the machine perception project at GMR. His research interests include geometric modeling model-based programming and control of intelligent automation systems.
No abstract available.
来源: 评论
Reactive High-level Behavior Synthesis for an Atlas Humanoid Robot
Reactive High-level Behavior Synthesis for an Atlas Humanoid...
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IEEE International Conference on robotics and Automation
作者: Spyros Maniatopoulos Philipp Schillinger Vitchyr Pong David C. Conner Hadas Kress-Gazit Verifiable Robotics Research Group Sibley School of Mechanical and Aerospace Engineering Cornell University Ithaca NY 14853 USA Robert Bosch GmbH Corporate Research Department for Cognitive Systems 70442 Stuttgart Germany Capable Humanitarian Robotics & Intelligent Systems Lab Department of Physics Computer Science and Engineering Christopher Newport University Newport News VA 23606 USA
In this work, we take a step towards bridging the gap between the theory of formal synthesis and its application to real-world, complex, robotic systems. In particular, we present an end-to-end approach for the automa... 详细信息
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Constrained Generative Sampling of 6-DoF Grasps
arXiv
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arXiv 2023年
作者: Lundell, Jens Verdoja, Francesco Le, Tran Nguyen Mousavian, Arsalan Fox, Dieter Kyrki, Ville Intelligent Robotics Group Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Finland KTH Royal Institute of Technology Sweden NVIDIA Corporation United States Paul G. Allen School of Computer Science & Engineering University of Washington Seattle United States
Most state-of-the-art data-driven grasp sampling methods propose stable and collision-free grasps uniformly on the target object. For bin-picking, executing any of those reachable grasps is sufficient. However, for co... 详细信息
来源: 评论
Data-Driven Analysis of Skin Cancer Classification with Convolutional Neural Networks for E-Health Applications
Data-Driven Analysis of Skin Cancer Classification with Conv...
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IEEE Conference on Global Communications (GLOBECOM)
作者: Imran Ahmed Misbah Ahmad Abdellah Chehri Gwanggil Jeon School of Computing and Information Science Anglia Ruskin University Cambridge UK Animal and Agriculture Department Hartpury University Gloucester UK Centre for Machine Vision Bristol Robotics Laboratory University of the West of England Bristol UK Department of Mathematics and Computer Science The Royal Military College of Canada (RMC) Canada Department of Embedded Systems Engineering Incheon National University Incheon Korea
This study explores the effectiveness of Convolutional Neural Networks (CNNs) in automatically classifying skin cancer for e-health applications. The trained model showcases impressive performance by leveraging the HA... 详细信息
来源: 评论
Integrated Bi-Manual Motion Generation and Control shaped for Probabilistic Movement Primitives
Integrated Bi-Manual Motion Generation and Control shaped fo...
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IEEE-RAS International Conference on Humanoid Robots
作者: Jonathan Vorndamme João Carvalho Riddhiman Laha Dorothea Koert Luis Figueredo Jan Peters Sami Haddadin Department of Computer Engineering Technische Universität München (TUM) TUM School of Computation Information and Technology (CIT) Munich Institute of Robotics and Machine Intelligence (MIRMI) Germany Intelligent Autonomous Systems group Technische Universitat Darmstadt (TUD) Germany Center for Cognitive Science TUD Germany
This work introduces a novel cooperative control framework that allows for real-time reactiveness and adaptation whilst satisfying implicit constraints stemming from proba-bilistic/stochastic trajectories. Stemming fr... 详细信息
来源: 评论