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Comprehensive Relation Modelling for Image Paragraph Generation 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 369-382
作者:  Xianglu Zhu;  Zhang Zhang;  Wei Wang;  Zilei Wang
Adobe PDF(1963Kb)  |  收藏  |  浏览/下载：4/2  |  提交时间：2024/04/23
Image paragraph generation, visual relationship, scene graph, graph convolutional network (GCN), long short-term memory  
Enhancing Multi-agent Coordination via Dual-channel Consensus 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 349-368
作者:  Qingyang Zhang;  Kaishen Wang;  Jingqing Ruan;  Yiming Yang;  Dengpeng Xing;  Bo Xu
Adobe PDF(4997Kb)  |  收藏  |  浏览/下载：5/2  |  提交时间：2024/04/23
Multi-agent reinforcement learning, contrastive representation learning, consensus, multi-agent cooperation, cognitive consistency  
Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 1, 页码: 197-214
作者:  Zihui Yan;  Yunlong Wang;  Kunbo Zhang;  Zhenan Sun;  Lingxiao He
Adobe PDF(3457Kb)  |  收藏  |  浏览/下载：5/1  |  提交时间：2024/04/23
Iris recognition, periocular recognition, spatial feature reconstruction, fully convolutional network, flexible matching, unsupervised iris quality assessment, adaptive weight fusion  
AI for Supporting the Freedom of Drawing 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 1, 页码: 63-88
作者:  Xiaohua Sun;  Juexiao Qin
Adobe PDF(14055Kb)  |  收藏  |  浏览/下载：4/1  |  提交时间：2024/04/23
Intention understanding, drawing support, drawing, art, human-artificial intelligence (AI) collaboration  
A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 614-639
作者:  Bolin Gao;  Keke Wan;  Qien Chen;  Zhou Wang;  Rui Li;  Yu Jiang;  Run Mei;  Yinghui Luo;  Keqiang Li
Adobe PDF(12630Kb)  |  收藏  |  浏览/下载：4/1  |  提交时间：2024/04/23
Predictive cruise control (PCC), cloud control system (CCS), cooperative control, efficient operation, intelligent connected vehicle  
Dynamic Movement Primitives Based Robot Skills Learning 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 396-407
作者:  Ling-Huan Kong;  Wei He;  Wen-Shi Chen;  Hui Zhang;  Yao-Nan Wang
Adobe PDF(3181Kb)  |  收藏  |  浏览/下载：5/2  |  提交时间：2024/04/23
Dynamic movement primitives (DMPs), trajectory tracking control, robot learning from demonstrations, neural networks (NNs), adaptive control  
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：4/1  |  提交时间：2024/04/23
Artificial intelligence (AI), edge intelligence (EI), distributed computing, deep neural network (DNN), collaborative inference  
A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-oriented Dialogue Policy Learning 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 318-334
作者:  Wai-Chung Kwan;  Hong-Ru Wang;  Hui-Min Wang;  Kam-Fai Wong
Adobe PDF(2211Kb)  |  收藏  |  浏览/下载：0/0  |  提交时间：2024/04/23
Dialogue policy learning (DPL), task-oriented dialogue system (TOD), reinforcement learning (RL), dialogue system, Markov decision process  
AI in Human-computer Gaming: Techniques, Challenges and Opportunities 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 299-317
作者:  Qi-Yue Yin;  Jun Yang;  Kai-Qi Huang;  Mei-Jing Zhao;  Wan-Cheng Ni;  Bin Liang;  Yan Huang;  Shu Wu;  Liang Wang
Adobe PDF(2608Kb)  |  收藏  |  浏览/下载：7/1  |  提交时间：2024/04/23
Human-computer gaming, AI, intelligent decision making, deep reinforcement learning, self-play  
Mitigating Spurious Correlations for Self-supervised Recommendation 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 2, 页码: 263-275
作者:  Xin-Yu Lin;  Yi-Yan Xu;  Wen-Jie Wang;  Yang Zhang;  Fu-Li Feng
Adobe PDF(2244Kb)  |  收藏  |  浏览/下载：3/1  |  提交时间：2024/04/23
Self-supervised recommendation  spurious correlations  spurious features  invariant feature learning  contrastive learning