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Dynamic Movement Primitives Based Robot Skills Learning 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 396-407
作者:  Ling-Huan Kong;  Wei He;  Wen-Shi Chen;  Hui Zhang;  Yao-Nan Wang
Adobe PDF(3181Kb)  |  收藏  |  浏览/下载：5/2  |  提交时间：2024/04/23
Dynamic movement primitives (DMPs), trajectory tracking control, robot learning from demonstrations, neural networks (NNs), adaptive control  
A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-oriented Dialogue Policy Learning 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 318-334
作者:  Wai-Chung Kwan;  Hong-Ru Wang;  Hui-Min Wang;  Kam-Fai Wong
Adobe PDF(2211Kb)  |  收藏  |  浏览/下载：0/0  |  提交时间：2024/04/23
Dialogue policy learning (DPL), task-oriented dialogue system (TOD), reinforcement learning (RL), dialogue system, Markov decision process  
Causal Reasoning Meets Visual Representation Learning: A Prospective Study 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 6, 页码: 485-511
作者:  Yang Liu;  Yu-Shen Wei;  Hong Yan;  Guan-Bin Li;  Liang Lin
Adobe PDF(3224Kb)  |  收藏  |  浏览/下载：4/0  |  提交时间：2024/04/23
Causal reasoning  visual representation learning  reliable artificial intelligence  spatial-temporal data  multi-modal analysis  
Facial-sketch Synthesis: A New Challenge 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 4, 页码: 257-287
作者:  Deng-Ping Fan;  Ziling Huang;  Peng Zheng;  Hong Liu;  Xuebin Qin;  Luc Van Gool
Adobe PDF(12340Kb)  |  收藏  |  浏览/下载：5/0  |  提交时间：2024/04/23
Facial sketch synthesis (FSS)  facial sketch dataset  benchmark  attribute  style transfer  
Probability Enhanced Entropy (PEE) Novel Feature for Improved Bird Sound Classification 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 1, 页码: 52-62
作者:  Ramashini Murugaiya;  Pg Emeroylariffion Abas;  Liyanage Chandratilak De Silva
Adobe PDF(1168Kb)  |  收藏  |  浏览/下载：4/2  |  提交时间：2024/04/23
Bird sounds  classification  Gammatone frequency cepstral coefficient (GTCC)  probability enhanced entropy (PEE)  support vector machine (SVM)  
A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 965-981
作者:  Yong-Chao Li;  Rui-Sheng Jia;  Ying-Xiang Hu;  Hong-Mei Sun
Adobe PDF(10448Kb)  |  收藏  |  浏览/下载：21/8  |  提交时间：2024/03/18
Crowd density estimation  linear feature calibration  vision transformer  weakly-supervision learning  
A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 760-781
作者:  Dingxin He;  HaoPing Wang;  Yang Tian;  Yida Guo
Adobe PDF(9812Kb)  |  收藏  |  浏览/下载：46/9  |  提交时间：2024/02/19
Adaptive control  input deadzone  model-free control  n-DOF upper-limb exoskeleton  neural network  
Fault Estimation for a Class of Markov Jump Piecewise-Affine Systems: Current Feedback Based Iterative Learning Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 418-429
作者:  Yanzheng Zhu;  Nuo Xu;  Fen Wu;  Xinkai Chen;  Donghua Zhou
Adobe PDF(5104Kb)  |  收藏  |  浏览/下载：33/12  |  提交时间：2024/01/23
Current feedback  fault estimation  iterative learning observer  Markov jump piecewise-affine system  
Advancements in Humanoid Robots: A Comprehensive Review and Future Prospects 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 301-328
作者:  Yuchuang Tong;  Haotian Liu;  Zhengtao Zhang
Adobe PDF(7587Kb)  |  收藏  |  浏览/下载：76/14  |  提交时间：2024/01/23
Future trends and challenges  humanoid robots  human-robot interaction  key technologies  potential applications  
Reinforcement Learning in Process Industries: Review and Perspective 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 283-300
作者:  Oguzhan Dogru;  Junyao Xie;  Om Prakash;  Ranjith Chiplunkar;  Jansen Soesanto;  Hongtian Chen;  Kirubakaran Velswamy;  Fadi Ibrahim;  Biao Huang
Adobe PDF(1275Kb)  |  收藏  |  浏览/下载：37/13  |  提交时间：2024/01/23
Process control  process systems engineering  reinforcement learning