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Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 6, 页码: 822-836
作者:  Kai Zhang;  Yawei Li;  Jingyun Liang;  Jiezhang Cao;  Yulun Zhang;  Hao Tang;  Deng-Ping Fan;  Radu Timofte;  Luc Van Gool
Adobe PDF(7952Kb)  |  收藏  |  浏览/下载：32/12  |  提交时间：2024/04/23
Blind image denoising, real image denosing data synthesis, Transformer, image signal processing (ISP) pipeline  
Federated Learning on Multimodal Data: A Comprehensive Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 539-553
作者:  Yi-Ming Lin;   Yuan Gao;  Mao-Guo Gong;  Si-Jia Zhang;  Yuan-Qiao Zhang;  Zhi-Yuan Li
Adobe PDF(1253Kb)  |  收藏  |  浏览/下载：19/7  |  提交时间：2024/04/23
Federated learning, multimodal learning, heterogeneous data, edge computing, collaborative learning  
A Survey on Collaborative DNN Inference for Edge Intelligence 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 370-395
作者:  Wei-Qing Ren;  Yu-Ben Qu;  Chao Dong;  Yu-Qian Jing;  Hao Sun;  Qi-Hui Wu;  Song Guo
Adobe PDF(2969Kb)  |  收藏  |  浏览/下载：38/11  |  提交时间：2024/04/23
Artificial intelligence (AI), edge intelligence (EI), distributed computing, deep neural network (DNN), collaborative inference  
Pruning-aware Sparse Regularization for Network Pruning 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 1, 页码: 109-120
作者:  Nan-Fei Jiang
Adobe PDF(1665Kb)  |  收藏  |  浏览/下载：36/12  |  提交时间：2024/04/23
Deep learning  convolutional neural network (CNN)  model compression and acceleration  network pruning  regularization  
AUTOSIM: Automated Urban Traffic Operation Simulation via Meta-Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1871-1881
作者:  Yuanqi Qin;  Wen Hua;  Junchen Jin;  Jun Ge;  Xingyuan Dai;  Lingxi Li;  Xiao Wang;  Fei-Yue Wang
Adobe PDF(3244Kb)  |  收藏  |  浏览/下载：113/21  |  提交时间：2023/08/10
Conditional generative adversarial network  signalized urban networks  short-term link speed prediction  
Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1822-1833
作者:  Wei Xu;  Chen Zhao;  Jie Cheng;  Yin Wang;  Yiqing Tang;  Tao Zhang;  Zhiming Yuan;  Yisheng Lv;  Fei-Yue Wang
Adobe PDF(3484Kb)  |  收藏  |  浏览/下载：132/62  |  提交时间：2023/08/10
High-speed railway  reinforcement learning  train timetable rescheduling  Transformer  
How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1781-1796
作者:  Hongyi Lin;  Yang Liu;  Shen Li;  Xiaobo Qu
Adobe PDF(1497Kb)  |  收藏  |  浏览/下载：203/122  |  提交时间：2023/08/10
Autonomous driving  generative adversarial network (GAN)  intelligent transportation system (ITS)  traffic anomaly inspection  traffic flow  
Steps Toward Industry 5.0: Building “6S” Parallel Industries With Cyber-Physical-Social Intelligence 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 8, 页码: 1692-1703
作者:  Xingxia Wang;  Jing Yang;  Yutong Wang;  Qinghai Miao;  Fei-Yue Wang;  Aijun Zhao;  Jian-Ling Deng;  Lingxi Li;  Xiaoxiang Na;  Ljubo Vlacic
Adobe PDF(15811Kb)  |  收藏  |  浏览/下载：142/28  |  提交时间：2023/07/20
ACP  artificial intelligence  CPS  CPSS  Industry 4.0  Industry 5.0  parallel industries  parallel intelligence  
Hyperspectral Image Super-Resolution Meets Deep Learning: A Survey and Perspective 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 8, 页码: 1668-1691
作者:  Xinya Wang;  Qian Hu;  Yingsong Cheng;  Jiayi Ma
Adobe PDF(22541Kb)  |  收藏  |  浏览/下载：105/20  |  提交时间：2023/07/20
Deep learning  hyperspectral image  image fusion  image super-resolution  survey  
Pavement Cracks Coupled With Shadows: A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1593-1607
作者:  Lili Fan;  Shen Li;  Ying Li;  Bai Li;  Dongpu Cao;  Fei-Yue Wang
Adobe PDF(23502Kb)  |  收藏  |  浏览/下载：113/14  |  提交时间：2023/06/14
Automatic pavement crack detection  data augmentation compensation  deep learning  residual feature augmentation  shadow removal  shadow-crack dataset