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A Framework and Operational Procedures for Metaverses-Based Industrial Foundation Models 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 页码: 10
作者:  Wang, Jiangong;  Tian, Yonglin;  Wang, Yutong;  Yang, Jing;  Wang, Xingxia;  Wang, Sanjin;  Kwan, Oliver
Adobe PDF(3322Kb)  |  收藏  |  浏览/下载：122/33  |  提交时间：2023/02/22
Cyber-physical-social intelligence (CPSI)  cyber-physical-social systems (CPSSs)  industrial foundation models (IFMs)  intelligent enterprises  metaverses  operational processes  parallel intelligence  
Cross-Architecture Knowledge Distillation 会议论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, Macau SAR, China, 2022.12.4-2022.12.8
作者:  Yufan Liu;  Jiajiong Cao;  Bing Li;  Weiming Hu;  Jingting Ding;  Liang Li
Adobe PDF(1020Kb)  |  收藏  |  浏览/下载：129/41  |  提交时间：2023/04/23
Knowledge distillation  Cross architecture  Model compression  Deep learning  
Learning adversarial point-wise domain alignment for stereo matching 期刊论文
NEUROCOMPUTING, 2022, 卷号: 491, 页码: 564-574
作者:  Zhang, Chenghao;  Meng, Gaofeng;  Xu, Richard Yi Da;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(3885Kb)  |  收藏  |  浏览/下载：241/47  |  提交时间：2022/09/19
Stereo Matching  Domain adaptation  Point-wise linear transformation  Adversarial learning  
Toward few-shot domain adaptation with perturbation-invariant representation and transferable prototypes 期刊论文
FRONTIERS OF COMPUTER SCIENCE, 2022, 卷号: 16, 期号: 3, 页码: 11
作者:  Fan, Junsong;  Wang, Yuxi;  Guan, He;  Song, Chunfeng;  Zhang, Zhaoxiang
Adobe PDF(4804Kb)  |  收藏  |  浏览/下载：255/44  |  提交时间：2022/06/10
domain adaptation  semantic segmentation  
Learning Accurate and Stable Point-to-Point Motions: A Dynamic System Approach 期刊论文
IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 卷号: 7, 期号: 2, 页码: 1510-1517
作者:  Zhang, Yu;  Cheng, Long;  Li, Houcheng;  Cao, Ran
Adobe PDF(3334Kb)  |  收藏  |  浏览/下载：200/19  |  提交时间：2022/02/16
Point-to-point tasks  neural network  dynamic system  generalization performance  high dimensional data  
Instance segmentation of biological images using graph convolutional network 期刊论文
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2022, 卷号: 110, 页码: 10
作者:  Xu, Rongtao;  Li, Ye;  Wang, Changwei;  Xu, Shibiao;  Meng, Weiliang;  Zhang, Xiaopeng
Adobe PDF(2815Kb)  |  收藏  |  浏览/下载：243/46  |  提交时间：2022/07/25
Instance segmentation  Biological images  GCN  Spatial attention  Graph-guided feature fusion  Instance segmentation  Biological images  GCN  Spatial attention  Graph-guided feature fusion  
SurgiNet: Pyramid Attention Aggregation and Class-wise Self-Distillation for Surgical Instrument Segmentation 期刊论文
MEDICAL IMAGE ANALYSIS, 2022, 卷号: 76, 页码: 102310
作者:  Ni, Zhen-Liang;  Zhou, Xiao-Hu;  Wang, Guan-An;  Yue, Wen-Qian;  Li, Zhen;  Bian, Gui-Bin;  Hou, Zeng-Guang
Adobe PDF(1944Kb)  |  收藏  |  浏览/下载：491/203  |  提交时间：2022/02/16
Surgical Insturment Segmentation  Class-wise Self-Distillation  Pyramid Attention  
PSNet: Perspective-sensitive convolutional network for object detection 期刊论文
NEUROCOMPUTING, 2022, 卷号: 468, 页码: 384-395
作者:  Zhang, Xin;  Liu, Yicheng;  Huo, Chunlei;  Xu, Nuo;  Wang, Lingfeng;  Pan, Chunhong
Adobe PDF(8656Kb)  |  收藏  |  浏览/下载：274/36  |  提交时间：2021/12/28
Object detection  Perspective-sensitive  Structural neural network  
PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling 期刊论文
IEEE Transactions on Image Processing, 2022, 卷号: 31, 页码: 5121-5133
作者:  Yang, Li;  Xu, Yan;  Wang, Shaoru;  Yuan, Chunfeng;  Zhang, Ziqi;  Li, Bing;  Hu, Weiming
Adobe PDF(3190Kb)  |  收藏  |  浏览/下载：207/32  |  提交时间：2022/09/19
Object detection  prediction decoupling  convolutional neural network  
An Efficient Sampling-Based Attention Network for Semantic Segmentation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 2850-2863
作者:  He, Xingjian;  Liu, Jing;  Wang, Weining;  Lu, Hanqing
Adobe PDF(3252Kb)  |  收藏  |  浏览/下载：322/74  |  提交时间：2022/06/10
Stochastic processes  Sampling methods  Semantics  Image segmentation  Computational complexity  Pattern recognition  Convolution  Semantic segmentation  stochastic sampling-based attention  deterministic sampling-based attention