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Industry-oriented Detection Method of PCBA Defects Using Semantic Segmentation Models 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1438-1446
作者:  Yang Li;  Xiao Wang;  Zhifan He;  Ze Wang;  Ke Cheng;  Sanchuan Ding;  Yijing Fan;  Xiaotao Li;  Yawen Niu;  Shanpeng Xiao;  Zhenqi Hao;  Bin Gao;  Huaqiang Wu
Adobe PDF(12898Kb)  |  收藏  |  浏览/下载：38/10  |  提交时间：2024/05/22
Automated optical inspection (AOI)  deep learning  defect detection  printed circuit board assembly (PCBA)  semantic segmentation  
Multi-Axis Attention With Convolution Parallel Block for Organoid Segmentation 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1295-1297
作者:  Pengwei Hu;  Xun Deng;  Feng Tan;  Lun Hu
Adobe PDF(1525Kb)  |  收藏  |  浏览/下载：76/24  |  提交时间：2024/04/10
A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 824-850
作者:  M. Victoria Luzón;  Nuria Rodríguez-Barroso;  Alberto Argente-Garrido;  Daniel Jiménez-López;  Jose M. Moyano;  Javier Del Ser;  Weiping Ding;  Francisco Herrera
Adobe PDF(4602Kb)  |  收藏  |  浏览/下载：53/17  |  提交时间：2024/03/18
Data privacy  distributed machine learning  federated learning  software frameworks  
Sparse Reconstructive Evidential Clustering for Multi-View Data 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 459-473
作者:  Chaoyu Gong;  Yang You
Adobe PDF(1769Kb)  |  收藏  |  浏览/下载：89/43  |  提交时间：2024/01/23
Evidence theory  multi-view clustering (MVC)  optimization  sparse reconstruction  
Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 231-239
作者:  Yahui Liu;  Bin Tian;  Yisheng Lv;  Lingxi Li;  Fei-Yue Wang
Adobe PDF(8541Kb)  |  收藏  |  浏览/下载：281/168  |  提交时间：2024/01/02
Content-based Transformer  deep learning  feature aggregator  local attention  point cloud classification  
Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 74-87
作者:  Bogang Qu;  Zidong Wang;  Bo Shen;  Hongli Dong;  Hongjian Liu
Adobe PDF(2856Kb)  |  收藏  |  浏览/下载：151/75  |  提交时间：2024/01/02
Decentralized state estimation (SE)  measurements with anomalies  minimum error entropy  unscented Kalman filter  wide-area power systems  
Knowledge Transfer Learning via Dual Density Sampling for Resource-Limited Domain Adaptation 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 12, 页码: 2269-2291
作者:  Zefeng Zheng;  Luyao Teng;  Wei Zhang;  Naiqi Wu;  Shaohua Teng
Adobe PDF(15412Kb)  |  收藏  |  浏览/下载：140/25  |  提交时间：2023/10/31
Cross-domain risk  dual density sampling  intra-domain risk  maximum mean discrepancy  knowledge transfer learning  resource-limited domain adaptation  
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：107/20  |  提交时间：2023/07/20
Deep learning  hyperspectral image  image fusion  image super-resolution  survey  
A Fast Clustering Based Evolutionary Algorithm for Super-Large-Scale Sparse Multi-Objective Optimization 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 4, 页码: 1048-1063
作者:  Ye Tian;  Yuandong Feng;  Xingyi Zhang;  Changyin Sun
Adobe PDF(2003Kb)  |  收藏  |  浏览/下载：374/110  |  提交时间：2023/03/22
Evolutionary computation  fast clustering  sparse multi-objective optimization  super-large-scale optimization  
Squeezing More Past Knowledge for Online Class-Incremental Continual Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 3, 页码: 722-736
作者:  Da Yu;  Mingyi Zhang;  Mantian Li;  Fusheng Zha;  Junge Zhang;  Lining Sun;  Kaiqi Huang
Adobe PDF(7599Kb)  |  收藏  |  浏览/下载：277/101  |  提交时间：2023/03/02
Catastrophic forgetting  class-incremental learning  continual learning (CL)  experience replay