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Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overview 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1106-1126
作者:  Wenqi Ren;  Yang Tang;  Qiyu Sun;  Chaoqiang Zhao;  Qing-Long Han
Adobe PDF(12695Kb)  |  收藏  |  浏览/下载：11/2  |  提交时间：2024/04/10
Computer vision  deep learning  few-shot learning  low-shot learning  semantic segmentation  zero-shot learning  
Advancements in Humanoid Robots: A Comprehensive Review and Future Prospects 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 301-328
作者:  Yuchuang Tong;  Haotian Liu;  Zhengtao Zhang
Adobe PDF(7587Kb)  |  收藏  |  浏览/下载：72/14  |  提交时间：2024/01/23
Future trends and challenges  humanoid robots  human-robot interaction  key technologies  potential applications  
Coarse-to-Fine Video Instance Segmentation With Factorized Conditional Appearance Flows 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 5, 页码: 1192-1208
作者:  Zheyun Qin;  Xiankai Lu;  Xiushan Nie;  Dongfang Liu;  Yilong Yin;  Wenguan Wang
Adobe PDF(42794Kb)  |  收藏  |  浏览/下载：78/23  |  提交时间：2023/04/26
Embedding learning  generative model  normalizing flows  video instance segmentation (VIS)  
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：100/23  |  提交时间：2023/07/20
ACP  artificial intelligence  CPS  CPSS  Industry 4.0  Industry 5.0  parallel industries  parallel intelligence  
STGSA: A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 1, 页码: 226-238
作者:  Zebing Wei;  Hongxia Zhao;  Zhishuai Li;  Xiaojie Bu;  Yuanyuan Chen;  Xiqiao Zhang;  Yisheng Lv;  Fei-Yue Wang
Adobe PDF(7068Kb)  |  收藏  |  浏览/下载：244/62  |  提交时间：2023/01/03
Deep learning  graph neural network (GNN)  multi-stream  spatial-temporal feature extraction  temporal graph  traffic prediction  
Current-Aided Multiple-AUV Cooperative Localization and Target Tracking in Anchor-Free Environments 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 3, 页码: 792-806
作者:  Yichen Li;  Wenbin Yu;  Xinping Guan
Adobe PDF(3498Kb)  |  收藏  |  浏览/下载：131/35  |  提交时间：2023/03/02
Anchor-free  belief propagation  cooperative localization  current-aided  target tracking  
Complex-Valued Neural Networks: A Comprehensive Survey 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 8, 页码: 1406-1426
作者:  ChiYan Lee;  Hideyuki Hasegawa;  Shangce Gao
Adobe PDF(1612Kb)  |  收藏  |  浏览/下载：185/40  |  提交时间：2022/08/01
Complex activation function  complex backpropagation algorithm  complex-valued learning algorithm  complex-valued neural network  deep learning  
Integrated Inspection of QoM, QoP, and QoS for AOI Industries in Metaverses 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 12, 页码: 2071-2078
作者:  Yutong Wang;  Yonglin Tian;  Jiangong Wang;  Yansong Cao;  Shixing Li;  Bin Tian
Adobe PDF(1477Kb)  |  收藏  |  浏览/下载：199/78  |  提交时间：2022/12/02
Automated Optical Inspection  Metaverses  Quality Inspection  Transformers  
Large-Scale Group Decision Making: A Systematic Review and a Critical Analysis 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 6, 页码: 949-966
作者:  Diego García-Zamora;  Álvaro Labella;  Weiping Ding;  Rosa M. Rodríguez;  Luis Martínez
Adobe PDF(11684Kb)  |  收藏  |  浏览/下载：126/14  |  提交时间：2022/05/30
Challenges  large-scale consensus models  large-scale group decision making (LSGDM)  systematic review  
Visuals to Text: A Comprehensive Review on Automatic Image Captioning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 8, 页码: 1339-1365
作者:  Yue Ming;  Nannan Hu;  Chunxiao Fan;  Fan Feng;  Jiangwan Zhou;  Hui Yu
Adobe PDF(56128Kb)  |  收藏  |  浏览/下载：150/21  |  提交时间：2022/08/01
Artificial intelligence  attention mechanism  encoder-decoder framework  image captioning  multi-modal understanding  training strategies