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Digital Twin Driven Measurement in Robotic Flexible Printed Circuit Assembly 期刊论文
IEEE Transactions on Instrumentation & Measurement, 2023, 卷号: 72, 页码: 5007812
作者:  Yang Minghao;  Huang Zhenping;  Sun Yangchang;  Zhao Yongjia;  Sun Ruize;  Sun Qi;  Chen JinLong;  Qiang BaoHua;  Wang JingHong;  Sun FuChun
Adobe PDF(39985Kb)  |  收藏  |  浏览/下载：15/3  |  提交时间：2024/06/24
Large sequence models for sequential decision-making: a survey 期刊论文
FRONTIERS OF COMPUTER SCIENCE, 2023, 卷号: 17, 期号: 6, 页码: 18
作者:  Wen, Muning;  Lin, Runji;  Wang, Hanjing;  Yang, Yaodong;  Wen, Ying;  Mai, Luo;  Wang, Jun;  Zhang, Haifeng;  Zhang, Weinan
Adobe PDF(1351Kb)  |  收藏  |  浏览/下载：136/1  |  提交时间：2023/11/17
sequential decision-making  sequence modeling  the Transformer  training system  
EventMix: An efficient data augmentation strategy for event-based learning 期刊论文
Information Sciences, 2023, 卷号: 644, 页码: 11
作者:  Shen, Guobin;  Zhao, Dongcheng;  Zeng, Yi
Adobe PDF(2595Kb)  |  收藏  |  浏览/下载：113/4  |  提交时间：2023/11/17
Event based data augmentation  Neuromorphic data  Spiking neural networks  Reasonable label assignment  Gaussian mixture model  
SMIN: Semi-Supervised Multi-Modal Interaction Network for Conversational Emotion Recognition 期刊论文
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2023, 卷号: 14, 期号: 3, 页码: 2415-2429
作者:  Lian, Zheng;  Liu, Bin;  Tao, Jianhua
Adobe PDF(2103Kb)  |  收藏  |  浏览/下载：143/7  |  提交时间：2023/11/15
Emotion recognition  Feature extraction  Training  Acoustics  Semisupervised learning  Benchmark testing  Hidden Markov models  Semi-supervised multi-modal interaction network (SMIN)  conversational emotion recognition  semi-supervised learning  intra-modal interaction  cross-modal interaction  
A neural network based framework for variable impedance skills learning from demonstrations 期刊论文
ROBOTICS AND AUTONOMOUS SYSTEMS, 2023, 卷号: 160, 页码: 10
作者:  Zhang, Yu;  Cheng, Long;  Cao, Ran;  Li, Houcheng;  Yang, Chenguang
Adobe PDF(3824Kb)  |  收藏  |  浏览/下载：376/67  |  提交时间：2023/02/22
Variable impedance skill  Learning from demonstrations  Skills learning  Human-robot interaction