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基于突触巩固机制的前馈小世界神经网络设计 期刊论文
自动化学报, 2023, 卷号: 49, 期号: 10, 页码: 2145-2158
作者:  李文静;  李治港;  乔俊飞
Adobe PDF(1724Kb)  |  收藏  |  浏览/下载：13/6  |  提交时间：2024/04/24
小世界神经网络  突触巩固机制  网络正则化  重连规则  Wilcoxon符号秩检验  
Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 447-482
作者:  Xiao Wang;  Guangyao Chen;  Guangwu Qian;  Pengcheng Gao;  Xiao-Yong Wei;  Yaowei Wang;  Yonghong Tian;  Wen Gao
Adobe PDF(3540Kb)  |  收藏  |  浏览/下载：49/9  |  提交时间：2024/04/23
Multi-modal (MM), pre-trained model (PTM), information fusion, representation learning, deep learning  
Symmetric-threshold ReLU for Fast and Nearly Lossless ANN-SNN Conversion 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 435-446
作者:  Jianing Han;  Ziming Wang;  Jiangrong Shen;  Huajin Tang
Adobe PDF(1513Kb)  |  收藏  |  浏览/下载：38/15  |  提交时间：2024/04/23
Symmetric-threshold rectified linear unit (stReLU), deep spiking neural networks, artificial neural network-spiking neural network (ANN-SNN) conversion, lossless conversion, double thresholds  
VLP: A Survey on Vision-language Pre-training 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 1, 页码: 38-56
作者:  Fei-Long Chen;  Du-Zhen Zhang;  Ming-Lun Han;  Xiu-Yi Chen;  Jing Shi;  Shuang Xu;  Bo Xu
Adobe PDF(1427Kb)  |  收藏  |  浏览/下载：42/13  |  提交时间：2024/04/23
Vision and language  pre-training  transformers  multimodal learning  representation learning  
Cascading Delays for the High-Speed Rail Network Under Different Emergencies: A Double Layer Network Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 10, 页码: 2014-2025
作者:  Xingtang Wu;  Mingkun Yang;  Wenbo Lian;  Min Zhou;  Hongwei Wang;  Hairong Dong
Adobe PDF(2179Kb)  |  收藏  |  浏览/下载：145/50  |  提交时间：2023/09/07
Delay propagation  double layer network  high speed rail network  max-plus algebra  
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：134/62  |  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：206/123  |  提交时间：2023/08/10
Autonomous driving  generative adversarial network (GAN)  intelligent transportation system (ITS)  traffic anomaly inspection  traffic flow  
RGCNU: Recurrent Graph Convolutional Network With Uncertainty Estimation for Remaining Useful Life Prediction 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1640-1642
作者:  Qiwu Zhu;  Qingyu Xiong;  Zhengyi Yang;  Yang Yu
Adobe PDF(438Kb)  |  收藏  |  浏览/下载：160/33  |  提交时间：2023/06/14
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：114/14  |  提交时间：2023/06/14
Automatic pavement crack detection  data augmentation compensation  deep learning  residual feature augmentation  shadow removal  shadow-crack dataset  
Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 6, 页码: 1361-1387
作者:  Sibo Cheng;  César Quilodrán-Casas;  Said Ouala;  Alban Farchi;  Che Liu;  Pierre Tandeo;  Ronan Fablet;  Didier Lucor;  Bertrand Iooss;  Julien Brajard;  Dunhui Xiao;  Tijana Janjic;  Weiping Ding;  Yike Guo;  Alberto Carrassi;  Marc Bocquet;  Rossella Arcucci
Adobe PDF(17725Kb)  |  收藏  |  浏览/下载：113/30  |  提交时间：2023/05/29
Data assimilation (DA)  deep learning  machine learning (ML)  reduced-order-modelling  uncertainty quantification (UQ)