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Efficient Remote Sensing Image Super-Resolution via Lightweight Diffusion Models 期刊论文
IEEE Geoscience and Remote Sensing Letters, 2024, 卷号: 21, 页码: 1-5
作者:  An T(安泰);  Xue B(薛斌);  Huo CL(霍春雷);  Xiang SM(向世明);  Pan CH(潘春洪)
Adobe PDF(30422Kb)  |  收藏  |  浏览/下载：100/22  |  提交时间：2024/01/17
Remote sensing super-resolution  lightweight diffusion models  cross-attention mechanism  satellite imagery  
Multi-Agent Reinforcement Learning for Extended Flexible Job Shop Scheduling 期刊论文
MACHINES, 2024, 卷号: 12, 期号: 1, 页码: 25
作者:  Peng, Shaoming;  Xiong, Gang;  Yang, Jing;  Shen, Zhen;  Tamir, Tariku Sinshaw;  Tao, Zhikun;  Han, Yunjun;  Wang, Fei-Yue
收藏  |  浏览/下载：40/0  |  提交时间：2024/03/13
production planning and scheduling  multi-agent reinforcement learning  flexible job shop  path flexibility  technological flexibility  
Biphasic Face Photo-Sketch Synthesis via Semantic-Driven Generative Adversarial Network With Graph Representation Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 14
作者:  Qi, Xingqun;  Sun, Muyi;  Wang, Zijian;  Liu, Jiaming;  Li, Qi;  Zhao, Fang;  Zhang, Shanghang;  Shan, Caifeng
Adobe PDF(6718Kb)  |  收藏  |  浏览/下载：80/31  |  提交时间：2024/02/22
Face photo-sketch synthesis  generative adversarial network  graph representation learning  intraclass and interclass  iterative cycle training (ICT)  
Finite-time filtering of T-S fuzzy semi-Markov jump systems with asynchronous mode-dependent delays 期刊论文
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2023, 卷号: 360, 期号: 16, 页码: 12707-12728
作者:  Ma, Chao;  Fu, Hang;  Wu, Wei
收藏  |  浏览/下载：27/0  |  提交时间：2024/02/22
Memory-based Human Postural Regulation Control: An Asynchronous Semi-Markov Model Approach 期刊论文
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2023, 卷号: 21, 期号: 10, 页码: 3357-3367
作者:  Ma, Chao;  Fu, Hang;  Wu, Wei
收藏  |  浏览/下载：59/0  |  提交时间：2023/11/16
Asynchronous regulation  convex optimization  human postural regulation  memory-based regulation  semi-Markov jump system  
A Data-Driven Iterative Learning Approach for Optimizing the Train Control Strategy 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, 卷号: 19, 期号: 7, 页码: 7885-7893
作者:  Su, Shuai;  Zhu, Qingyang;  Liu, Junqing;  Tang, Tao;  Wei, Qinglai;  Cao, Yuan
收藏  |  浏览/下载：83/0  |  提交时间：2023/11/17
Deep reinforcement learning (RL)  driving strategy  energy-efficient train control (EETC)  soft actorcritic (SAC)  
PiCor: Multi-Task Deep Reinforcement Learning with Policy Correction 会议论文
Proceedings of the AAAI Conference on Artificial Intelligence, 美国 华盛顿, 2023.02.07 - 2023.02.14
作者:  Bai FS(白丰硕);  Zhang HM(张鸿铭);  Tao TY(陶天阳);  Wu ZH(武志亨);  Wang YN(王燕娜);  Xu B(徐博)
Adobe PDF(1663Kb)  |  收藏  |  浏览/下载：161/37  |  提交时间：2023/07/05
Reinforcement Learning Algorithms  Transfer  Domain Adaptation  Multi-Task Learning  
Sample-Observed Soft Actor-Critic Learning for Path Following of a Biomimetic Underwater Vehicle 期刊论文
IEEE Transactions on Automation Science and Engineering, 2023, 页码: 1-10
作者:  Ma, Ruichen;  Wang, Yu;  Wang, Shuo;  Cheng, Long;  Wang, Rui;  Tan, Ming
Adobe PDF(2902Kb)  |  收藏  |  浏览/下载：163/52  |  提交时间：2023/08/03
Event-Triggered Deep Reinforcement Learning Using Parallel Control: A Case Study in Autonomous Driving 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 卷号: 8, 期号: 4, 页码: 2821-2831
作者:  Lu, Jingwei;  Han, Liyuan;  Wei, Qinglai;  Wang, Xiao;  Dai, Xingyuan;  Wang, Fei-Yue
收藏  |  浏览/下载：75/0  |  提交时间：2023/11/17
Autonomous vehicles  Decision making  Path planning  Training  Optimal control  Deep learning  Complex systems  Autonomous driving  deep reinforcement learning  deep Q-network  event-triggered control  parallel control  
Dependency-Aware Vehicular Task Scheduling Policy for Tracking Service VEC Networks 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 卷号: 8, 期号: 3, 页码: 2400-2414
作者:  Li, Chao;  Liu, Fagui;  Wang, Bin;  Chen, C. L. Philip;  Tang, Xuhao;  Jiang, Jun;  Liu, Jie
收藏  |  浏览/下载：90/0  |  提交时间：2023/11/17
Task analysis  Intelligent vehicles  Optimization  Processor scheduling  Vehicle dynamics  Heuristic algorithms  Costs  Deep reinforcement learning (DRL)  scheduling policy  tracking service  vehicular edge computing (VEC)