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984 result(s) for “Deep Learning Methods” Page 1 of 20
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Learning Deep Dynamical Systems Using Stable Neural ODEs
Andreas Sochopoulos, Michael Gienger, Sethu Vijayakumar
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Keyframe Selection Via Deep Reinforcement Learning for Skeleton-Based Gesture Recognition
minggang gan, Jinting Liu, Yuxuan He, aobo chen, Qianzhao Ma
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Satellite-Model-Free Deep Learning Based Pose Estimation of Non-Cooperative Satellite and Tracking Using Navigation Filter
Shubham Shukla, Raunak Srivastava, Rolif Lima, Titas Bera
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Enhancing Safety Via Deep Reinforcement Learning in Trajectory Planning for Agile Flights within Unknown Environments
Lidia Rocha, Jorge Bidinotto, Fredrik Heintz, Mattias Tiger, Kelen Cristiane Teixeira Vivaldini
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Learning When to Stop: Efficient Active Tactile Perception with Deep Reinforcement Learning
Christopher Niemann, David Philip Leins, Luca Lach, Robert Haschke
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Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks
David Patricio Valencia Redrovan, Henry Williams, Yuning Xing, Trevor Gee, Minas Liarokapis, Bruce MacDonald
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Social Navigation in Crowded Environments with Model Predictive Control and Deep Learning-Based Human Trajectory Prediction
Viet-Anh Le, Behdad Chalaki, Vaishnav Tadiparthi, Hossein Nourkhiz Mahjoub, Jovin D'sa, Ehsan Moradi-Pari
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Mini-PointNetPlus: A Local Feature Descriptor in Deep Learning Model for Real-Time 3D Environment Perception
Chuanyu Luo, Nuo Cheng, Sikun Ma, Jun Xiang, Xiaohan Li, Shengguang Lei, Pu Li
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An Attention-Aware Deep Reinforcement Learning Framework for UAV-UGV Collaborative Route Planning
Mohammad Safwan Mondal, Subramanian Ramasamy, James Humann, Jim James, Dotterweich, Jean-Paul Reddinger, Marshal Childers, Pranav Bhounsule
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Real-Time Coordinated Motion Generation: A Hierarchical Deep Predictive Learning Model for Bimanual Tasks
Genki Shikada, Simon Armleder, Hiroshi Ito, Gordon Cheng, Tetsuya Ogata
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Collaboration Strategies for Two Heterogeneous Pursuers in A Pursuit-Evasion Game Using Deep Reinforcement Learning
Zhanping Zhong, Zhuoning Dong, Xiaoming Duan, Jianping He
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Temporal- and Viewpoint-Invariant Registration for Under-Canopy Footage using Deep-Learning-based Bird's-Eye View Prediction
Jiawei Zhou, Ruben Mascaro, Cesar Cadena Lerma, Margarita Chli, Lucas Teixeira
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DaFoEs: Mixing Datasets towards the Generalization of Vision-State Deep-Learning Force Estimation in Minimally Invasive Robotic Surgery
Mikel De Iturrate Reyzabal, Mingcong Chen, Wei Huang, Sebastien Ourselin, Hongbin Liu
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DeepMIF: Deep Monotonic Implicit Fields for Large-Scale LiDAR 3D Mapping
Kutay Yilmaz, Matthias Niessner, Anastasiia Kornilova, Alexey Artemov
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Deep Visual Odometry with Events and Frames
Roberto Pellerito, Marco Cannici, Daniel Gehrig, Joris Belhadj, Olivier Dubois-Matra, Massimo Casasco, Davide Scaramuzza
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DRIFT: Deep Reinforcement Learning for Intelligent Floating Platforms Trajectories
Matteo El Hariry, Antoine Richard, Vivek Muralidharan, Matthieu Geist, Miguel A. Olivares-Mendez
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Autonomous Landing on a Moving Platform Using Vision-Based Deep Reinforcement Learning
Pawel Ladosz, Meraj Mammadov, Heejung Shin, Woojae Shin, Hyondong Oh
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DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spatio-Temporal Propagation
Huixin Zhang, Guangming Wang, Xinrui Wu, Chenfeng Xu, Mingyu Ding, Masayoshi Tomizuka, Wei Zhan, Hesheng Wang
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TinyLidarNet: 2D Lidar-Based End-To-End Deep Learning Model for F1TENTH Autonomous Racing
Mohammed Misbah Zarrar, QiTao Weng, Bakhbyergyen Yerjan, Ahmet Soyyigit, Heechul Yun
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A Deep Reinforcement Learning Framework and Methodology for Reducing the Sim-to-Real Gap in ASV Navigation
Luis F. W. Batista, Junghwan Ro, Antoine Richard, Pete Schroepfer, Seth Hutchinson, Cedric Pradalier
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Bird's-Eye-View Trajectory Planning of Multiple Robots using Continuous Deep Reinforcement Learning and Model Predictive Control
Kristian Ceder, Ze Zhang, Adam Burman, Ilya Kuangaliyev, Krister Mattsson, Gabriel Nyman, Arvid Petersén, Lukas Wisell, Knut Akesson
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Uncertainty-Aware Deep Imitation Learning and Deployment for Autonomous Navigation through Crowded Intersections
Zeyu Zhu, Shuai Wang, Huijing Zhao
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Deep Ad-Hoc Sub-Team Partition Learning for Multi-Agent Air Combat Cooperation
Songyuan Fan, Haiyin Piao, Yi Hu, Feng Jiang, Roushu Yang
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Deep Reinforcement Learning-Based Large-Scale Robot Exploration
Yuhong Cao, Rui Zhao, Yizhuo Wang, Bairan Xiang, Guillaume Adrien Sartoretti
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Mitigating Adversarial Perturbations for Deep Reinforcement Learning Via Vector Quantization
Tung Luu, Thanh Nguyen, Joshua Tian Jin Tee, Sungwoong Kim, Chang D. Yoo
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MultipleCupSuctionNet: Deep Neural Network for Detecting Grasp Pose of a Vacuum Gripper with Multiple Suction Cups Based on YOLO Feature Map Affine Transformation
Ping Jiang, Kazuma Komoda, Haifeng Han, Jun'ichiro Ooga
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An End-To-End Deep Reinforcement Learning Based Modular Task Allocation Framework for Autonomous Mobile Systems
Song Ma, Jingqing Ruan, Yali Du, Richard Bucknall, Yuanchang Liu
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Binary Amplitude-Only Hologram Design for Acoustic End-Effector Construction by Physics-Based Deep Learning
Qing Liu, hu su, Jiaqi Li, Y.F. Li, zhiyuan ZHANG, Song LIU
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Deep Stochastic Kinematic Models for Probabilistic Motion Forecasting in Traffic
Laura Zheng, Sanghyun Son, Jing Liang, Xijun Wang, Brian Clipp, Ming C. Lin
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Accurate and Efficient Loop Closure Detection with Deep Binary Image Descriptor and Augmented Point Cloud Registration
Jialiang Wang, Zhi Gao, Zhipeng LIN, Zhiyu Zhou, Xiaonan Wang, Jianhua CHENG, Hao Zhang, Xinyi Liu, Ben M. Chen
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GDM-Net: Gas Distribution Mapping with a Mobile Robot Using Deep Reinforcement Learning and Gaussian Process Regression
Iliya Kulbaka, Ayan Dutta, Patrick Kreidl, Ladislau Bölöni, Swapnoneel Roy
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Deep Learning-Based Delay Compensation Framework for Teleoperated Wheeled Rovers on Soft Terrains
Ahmad Abubakar, Yahya Zweiri, Mubarak Yakubu, Ruqqayya Alhammadi, Mohammed Mohiuddin, Abdel Gafoor Haddad, Jorge Dias, Lakmal Seneviratne
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Socially Integrated Navigation: A Social Acting Robot with Deep Reinforcement Learning
Daniel Flögel, Lars Fischer, Thomas Rudolf, Tobias Schürmann, Sören Hohmann
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Adaptive Stochastic Nonlinear Model Predictive Control with Look-Ahead Deep Reinforcement Learning for Autonomous Vehicle Motion Control
Baha Zarrouki, Chenyang Wang, Johannes Betz
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Predicting Interaction Shape of Soft Continuum Robots Using Deep Visual Models
Yunqi Huang, Abdulaziz Y. Alkayas, Jialei Shi, Federico Renda, Helge Arne Wurdemann, Thomas George Thuruthel
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Enhancing Object Grasping Efficiency with Deep Learning and Post-Processing for Multi-Finger Robotic Hands
Pouya Samandi, Kamal Gupta, mehran mehrandezh
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Crowd-Aware Robot Navigation with Switching between Learning-Based and Rule-Based Methods Using Normalizing Flows
Kohei Matsumoto, Yuki Hyodo, Ryo Kurazume
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Multi-Agent Deep Reinforcement Learning for Persistent Monitoring with Sensing, Communication, and Localization Constraints
Manav Mishra, Prithvi Poddar, RAJAT AGRAWAL, Jingxi Chen, Pratap Tokekar, Sujit PB
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Roofus: Learning-Based Robotic Moisture Mapping on Flat Rooftops with Ground Penetrating Radar
Kevin Lee, Wei-Heng Lin, Talha Javed, Sruti Madhusudhan, Bilal Sher, Chen Feng
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Decentralized Multi-Robot Navigation Coupled with Spatial-Temporal RetNet Based on Deep Reinforcement Learning
Lin Chen, Yaonan Wang, Zhiqiang Miao, Mingtao Feng, Yuanzhe Wang, Yang Mo, zhen zhou, Hesheng Wang, Danwei Wang
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FNPG-NH: A Reinforcement Learning Framework for Flexible Needle Path Generation with Nonholonomic Constraints
Shah, Mukund,Patel, Niravkumar
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A Novel Variable Step-Size Path Planning Framework with Step Consistent Markov Decision Process for Large Scale UAV Swarm
Dan Xu, Yunxiao Guo, Han Long, Chang Wang
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SuPerPM: A Surgical Perception Framework Based on Deep Point Matching Learned from Physical Constrained Simulation Data
Shan Lin, Albert Miao, Ali Alabiad, Fei Liu, Kaiyuan Wang, Jingpei Lu, Florian Richter, Michael C. Yip
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DIVE: Deep Inertial-Only Velocity Aided Estimation for Quadrotors
Angad Bajwa, Charles Champagne Cossette, Mohammed Ayman Shalaby, James Richard Forbes
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A Deep Signed Directional Distance Function for Shape Representation
Ehsan Zobeidi, Nikolay Atanasov
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A Monte Carlo Approach to Koopman Direct Encoding and Its Application to the Learning of Neural-Network Observables
Nozawa, Itta,Kamienski, Emily,O'Neill, Cormac,Asada, Harry
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Deep Geometric Potential Functions for Tracking on Manifolds
Nikhil Potu Surya Prakash, Joohwan Seo, Koushil Sreenath, Jongeun Choi, Roberto HOROWITZ
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WSCLoc: Weakly-Supervised Sparse-View Camera Relocalization
jialu wang, kaichen zhou, Andrew Markham, Niki Trigoni
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VoxelContrast: Voxel Contrast-Based Unsupervised Learning for 3D Point Clouds
Yuxiang Qin, HAO SUN
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CASRL: Collision Avoidance with Spiking Reinforcement Learning among Dynamic, Decision-Making Agents
Chengjun Zhang, Ka-Wa Yip, Bo Yang, Zhiyong Zhang, Mengwen Yuan, Rui Yan, Huajin Tang
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