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Enhancing ENSO predictions with self-attention ConvLSTM and temporal embeddings 期刊论文
Frontiers in Marine Science, 2024, 卷号: 11, 页码: 1334210
作者:  Rui, Chuang;  Sun, Zhengya;  Zhang, Wensheng;  Liu, Anan;  Wei, Zhiqiang
Adobe PDF(14474Kb)  |  收藏  |  浏览/下载：36/10  |  提交时间：2024/05/28
El Niño-Southern Oscillation (ENSO)  deep learning for ENSO prediction  self-attention ConvLSTM  temporal embeddings  spring prediction barrier  
The Human Continuity Activity Semisupervised Recognizing Model for Multiview IoT Network 期刊论文
IEEE INTERNET OF THINGS JOURNAL, 2023, 卷号: 10, 期号: 11, 页码: 9398-9410
作者:  Yuan, Ruiwen;  Wang, Junping
Adobe PDF(1944Kb)  |  收藏  |  浏览/下载：106/4  |  提交时间：2023/11/17
Feature extraction  Sensors  Human activity recognition  Internet of Things  Data models  Sensor phenomena and characterization  Data mining  Activity feature extraction  deep learning  human activity recognition (HAR)  semisupervised learning  
Rethinking Pretraining as a Bridge From ANNs to SNNs 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 14
作者:  Lin, Yihan;  Hu, Yifan;  Ma, Shijie;  Yu, Dongjie;  Li, Guoqi
收藏  |  浏览/下载：335/0  |  提交时间：2023/03/20
Training  Task analysis  Neurons  Pipelines  Artificial neural networks  Feature extraction  Transfer learning  Event-driven dataset  neural network (NN) analysis  pretraining technique  spiking NN (SNN)  transfer learning  
Decentralized Autonomous Operations and Organizations in TransVerse: Federated Intelligence for Smart Mobility 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 卷号: 53, 期号: 4, 页码: 2062-2072
作者:  Zhao, Chen;  Dai, Xingyuan;  Lv, Yisheng;  Niu, Jinglong;  Lin, Yilun
Adobe PDF(1921Kb)  |  收藏  |  浏览/下载：283/6  |  提交时间：2023/02/22
Intelligent Transportation Systems (ITS)  Artificial Systems, Computational Experiments, Parallel Execution (ACP)  Cyber–Physical–Social Systems (CPSS)  
AutoMSNet: Multi-Source Spatio-Temporal Network via Automatic Neural Architecture Search for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 15
作者:  Fang, Shen;  Zhang, Chunxia;  Xiang, Shiming;  Pan, Chunhong
收藏  |  浏览/下载：169/0  |  提交时间：2023/02/22
Deep learning  neural architecture search  graph convolution  meta-learning  traffic flow prediction  
Subgraph-aware graph structure revision for spatial-temporal graph modeling 期刊论文
NEURAL NETWORKS, 2022, 卷号: 154, 页码: 190-202
作者:  Wang, Yuhu;  Zhang, Chunxia;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(1781Kb)  |  收藏  |  浏览/下载：200/10  |  提交时间：2023/01/09
Graph structure learning  Graph neural network  Spatial-temporal graph modeling  
ASCL: Adversarial supervised contrastive learning for defense against word substitution attacks 期刊论文
NEUROCOMPUTING, 2022, 卷号: 510, 页码: 59-68
作者:  Shi, Jiahui;  Li, Linjing;  Zeng, Daniel
Adobe PDF(1054Kb)  |  收藏  |  浏览/下载：271/33  |  提交时间：2022/11/14
Adversarial example  Adversarial training  Model robustness  Contrastive learning  Natural language processing  
Meta Graph Transformer: A Novel Framework for Spatial-Temporal Traffic Prediction 期刊论文
NEUROCOMPUTING, 2022, 卷号: 491, 页码: 544-563
作者:  Ye, Xue;  Fang, Shen;  Sun, Fang;  Zhang, Chunxia;  Xiang, Shiming
Adobe PDF(3491Kb)  |  收藏  |  浏览/下载：268/35  |  提交时间：2022/09/19
Traffic prediction  Spatial-temporal modeling  Meta-learning  Attention mechanism  Deep learning  
Explicit Cross-Modal Representation Learning for Visual Commonsense Reasoning 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 2986-2997
作者:  Zhang, Xi;  Zhang, Feifei;  Xu, Changsheng
Adobe PDF(5681Kb)  |  收藏  |  浏览/下载：413/4  |  提交时间：2022/07/25
Cognition  Video recording  Syntactics  Visualization  Task analysis  Semantics  Linguistics  Visual Commonsense Reasoning  explicit reasoning  syntactic structure  interpretability  
Scene captioning with deep fusion of images and point clouds 期刊论文
PATTERN RECOGNITION LETTERS, 2022, 卷号: 158, 页码: 9-15
作者:  Yu, Qiang;  Zhang, Chunxia;  Weng, Lubin;  Xiang, Shiming;  Pan, Chunhong
收藏  |  浏览/下载：220/0  |  提交时间：2022/07/25
Scene captioning  Point cloud  Deep fusion  Scene captioning  Point cloud  Deep fusion