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Diff-pcg: diffusion point cloud generation conditioned on continuous normalizing flow 期刊论文
The Visual Computer, 2024, 页码: 1-15
作者:  Yu T(余挺);  Meng WL(孟维亮);  Wu ZQ(吴仲琦);  Guo JW(郭建伟);  Zhang XP(张晓鹏)
Adobe PDF(2471Kb)  |  收藏  |  浏览/下载：22/6  |  提交时间：2024/06/11
3D shape generation  Diffusion model  Continuous normalizing flow  Point cloud  
The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0 期刊论文
Information Fusion, 2024, 卷号: 107, 页码: 1-16
作者:  Xiao Wang;  Yutong Wang;  Jing Yang;  Xiaofeng Jia;  Lijun Li;  Weiping Ding;  Fei-Yue Wang
Adobe PDF(4446Kb)  |  收藏  |  浏览/下载：29/2  |  提交时间：2024/06/06
Multi-source data fusion  CPSS  Industrial metaverses  Parallel manufacturing  Social manufacturing  
A memory and attention-based reinforcement learning for musculoskeletal robots with prior knowledge of muscle synergies 期刊论文
Robotic Intelligence and Automation, 2024, 卷号: 44, 期号: 2, 页码: 316-333
作者:  Xiaona Wang;  Jiahao Chen;  Hong Qiao
Adobe PDF(2591Kb)  |  收藏  |  浏览/下载：34/10  |  提交时间：2024/06/04
Musculoskeletal robot  Partial observable  Reinforcement learning  LSTM  Attention  Muscle synergy  
Robust Motion Learning for Musculoskeletal Robots Based on a Recurrent Neural Network and Muscle Synergies 期刊论文
IEEE Transactions on Automation Science and Engineering, 2024, 页码: 1-16
作者:  Jiahao Chen;  Wu YX(吴亚雄);  Yao CJ(姚超竞);  Huang X(黄销)
Adobe PDF(4084Kb)  |  收藏  |  浏览/下载：37/6  |  提交时间：2024/06/04
Musculoskeletal system  Robots  Muscles  Reinforcement learning  Robustness  Learning systems  Recurrent neural networks  Musculoskeletal robots  recurrent neural network  muscle synergy  robustness  
Graph-guided deep hashing networks for similar patient retrieval 期刊论文
Computers in Biology and Medicine, 2024, 卷号: 169, 页码: 107865
作者:  Gu, Yifan;  Yang, Xuebing;  Sun, Mengxuan;  Wang, Chutong;  Yang, Hongyu;  Yang, Chao;  Wang, Jinwei;  Kong, Guilan;  Lv, Jicheng;  Zhang, Wensheng
Adobe PDF(1325Kb)  |  收藏  |  浏览/下载：27/8  |  提交时间：2024/05/28
Similar patient retrieval  Deep hashing  Graph neural networks  Patient representation learning  Electronic health records  
Bionic Underwater Vehicle: A Data-Driven Disturbance Rejection Control Framework 期刊论文
IEEE ROBOTICS & AUTOMATION MAGAZINE, 2023, 卷号: 31, 期号: 1, 页码: 18-28
作者:  Wang, Kaihui;  Zou, Wei;  Ma, Ruichen;  Lv, Jiaqi;  Su, Hu;  Wang, Yu;  Ma, Hongxuan
Adobe PDF(2970Kb)  |  收藏  |  浏览/下载：69/7  |  提交时间：2024/02/22
Vehicle dynamics  Robots  Propulsion  Predictive models  Biological system modeling  Robustness  Disturbance observers  
Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13
作者:  Wang, Changwei;  Xu, Rongtao;  Xu, Shibiao;  Meng, Weiliang;  Xiao, Jun;  Zhang, Xiaopeng
Adobe PDF(4178Kb)  |  收藏  |  浏览/下载：154/12  |  提交时间：2023/12/21
Detailed representation transfer  lung nodules segmentation  medical images segmentation  soft mask  
CSIR: Cascaded Sliding CVAEs With Iterative Socially-Aware Rethinking for Trajectory Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 页码: 13
作者:  Zhou, Hao;  Yang, Xu;  Ren, Dongchun;  Huang, Hai;  Fan, Mingyu
Adobe PDF(4364Kb)  |  收藏  |  浏览/下载：91/1  |  提交时间：2023/11/17
Cascaded prediction  sliding sequence prediction  iterative social-aware rethinking  trajectory prediction  
Sand painting conversion based on detail preservation 期刊论文
COMPUTERS & GRAPHICS-UK, 2023, 卷号: 115, 页码: 371-381
作者:  Zhu, Mengting;  Yang, Meng;  Meng, Weiliang;  Li, Ping
Adobe PDF(4337Kb)  |  收藏  |  浏览/下载：47/5  |  提交时间：2023/11/17
Parameter optimization  Detail painting  Edge processing  
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation 期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2023, 卷号: 35, 期号: 9, 页码: 9154-9167
作者:  Zhang, Jinghao;  Zhu, Yanqiao;  Liu, Qiang;  Zhang, Mengqi;  Wu, Shu;  Wang, Liang
Adobe PDF(1134Kb)  |  收藏  |  浏览/下载：142/4  |  提交时间：2023/11/17
Multimedia recommendation  graph structure learning  contrastive learning