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Deep learning model for solar and wind energy forecasting considering Northwest China as an example Journal article
Li, Pengyu, Yang, Huiyu, Wu, Han, Wang, Yujia, Su, Hao, Zheng, Tianlong, Zhu, Fang, Zhang, Guangtao, Han, Yu. Deep learning model for solar and wind energy forecasting considering Northwest China as an example[J]. Results in Engineering, 2024, 24, 102939.
Authors:  Li, Pengyu;  Yang, Huiyu;  Wu, Han;  Wang, Yujia;  Su, Hao; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:6.0/5.6 | Submit date：2024/10/10
Attention-based Spatial-temporal Graph Neural Network  Deep Learning  Long Short-term Memory  Solar Energy  Wind Energy  
Multi-level traffic-responsive tilt camera surveillance through predictive correlated online learning Journal article
Li, Tao, Bian, Zilin, Lei, Haozhe, Zuo, Fan, Yang, Ya Ting, Zhu, Quanyan, Li, Zhenning, Ozbay, Kaan. Multi-level traffic-responsive tilt camera surveillance through predictive correlated online learning[J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2024, 167, 104804.
Authors:  Li, Tao;  Bian, Zilin;  Lei, Haozhe;  Zuo, Fan;  Yang, Ya Ting; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:7.6/9.6 | Submit date：2024/09/03
Real-time Traffic Surveillance  Online Learning Control  Spatial–temporal Forecasting  Traffic State Estimation  Dynamic Route Planning  
Weakly Supervised Monocular 3D Object Detection by Spatial-Temporal View Consistency Journal article
Han, Wencheng, Tao, Runzhou, Ling, Haibin, Shen, Jianbing. Weakly Supervised Monocular 3D Object Detection by Spatial-Temporal View Consistency[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.
Authors:  Han, Wencheng;  Tao, Runzhou;  Ling, Haibin;  Shen, Jianbing
Favorite | TC[Scopus]:0  IF:20.8/22.2 | Submit date：2024/10/10
Monocular 3d Object Detection  Production Cars Data  Spatial-temporal Consistency  Weakly Supervised Learning  
Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks Conference paper
Duan, Wenying, Fang, Tianxiang, Rao, Hong, He, Xiaoxi. Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks[C], New York, NY, USA:Association for Computing Machinery, 2024, 701-712.
Authors:  Duan, Wenying;  Fang, Tianxiang;  Rao, Hong;  He, Xiaoxi
Favorite | TC[Scopus]:0 | Submit date：2024/09/11
Lottery Ticket Hypothesis  Spatial-temporal Data Mining  Spatial-temporal Graph Neural Network  
FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction Conference paper
Yang, Linghua, Chen, Wantong, He, Xiaoxi, Wei, Shuyue, Xu, Yi, Zhou, Zimu, Tong, Yongxin. FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction[C], New York, NY, USA:Association for Computing Machinery, 2024, 6105–6116.
Authors:  Yang, Linghua;  Chen, Wantong;  He, Xiaoxi;  Wei, Shuyue;  Xu, Yi; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/09/11
Federated Learning  Traffic Prediction  Spatial-temporal Graph Neural Network  
A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility Journal article
Ling, Jiahao, Lan, Yuanchun, Huang, Xiaohui, Yang, Xiaofei. A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility[J]. Complex and Intelligent Systems, 2024, 10(3), 3305-3317.
Authors:  Ling, Jiahao;  Lan, Yuanchun;  Huang, Xiaohui;  Yang, Xiaofei
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:5.0/5.2 | Submit date：2024/05/16
Multivariate Time Series  Periodicity  Spatial–temporal  Traffic Forecasting  
A novel model for tourism demand forecasting with spatial–temporal feature enhancement and image-driven method Journal article
Dong, Yunxuan, Zhou, Binggui, Yang, Guanghua, Hou, Fen, Hu, Zheng, Ma, Shaodan. A novel model for tourism demand forecasting with spatial–temporal feature enhancement and image-driven method[J]. NEUROCOMPUTING, 2023, 556, 126663.
Authors:  Dong, Yunxuan;  Zhou, Binggui;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:4 TC[Scopus]:5  IF:5.5/5.5 | Submit date：2023/08/30
Deep Learning  Feature Enhancement  Spatial Series To Image Series  Spatial–temporal Learning  Tourism Demand Forecasting  
Localised Adaptive Spatial-Temporal Graph Neural Network Conference paper
Duan, Wenying, He, Xiaoxi, Zhou, Zimu, Thiele, Lothar, Rao, Hong. Localised Adaptive Spatial-Temporal Graph Neural Network[C]:ASSOC COMPUTING MACHINERY1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES, 2023, 448-458.
Authors:  Duan, Wenying;  He, Xiaoxi;  Zhou, Zimu;  Thiele, Lothar;  Rao, Hong
Favorite | TC[WOS]:1 TC[Scopus]:5 | Submit date：2024/01/10
Graph Sparsification  Spatial-temporal Data  Spatial-temporal Graph Neural Network  
Difference-guided multi-scale spatial-temporal representation for sign language recognition Journal article
Gao, Liqing, Hu, Lianyu, Lyu, Fan, Zhu, Lei, Wan, Liang, Pun, Chi Man, Feng, Wei. Difference-guided multi-scale spatial-temporal representation for sign language recognition[J]. Visual Computer, 2023, 39(8), 3417-3428.
Authors:  Gao, Liqing;  Hu, Lianyu;  Lyu, Fan;  Zhu, Lei;  Wan, Liang; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:3.0/3.0 | Submit date：2023/09/04
Key Spatial-temporal Representation  Multi-scale Sequence Alignment  Sign Language Recognition (Slr)  
A graph-attention based spatial-temporal learning framework for tourism demand forecasting Journal article
Zhou, Binggui, Dong, Yunxuan, Yang, Guanghua, Hou, Fen, Hu, Zheng, Xu, Suxiu, Ma, Shaodan. A graph-attention based spatial-temporal learning framework for tourism demand forecasting[J]. Knowledge-Based Systems, 2023, 263, 110275.
Authors:  Zhou, Binggui;  Dong, Yunxuan;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:6 TC[Scopus]:8  IF:7.2/7.4 | Submit date：2023/04/03
Tourism Demand Forecasting  Dynamic Spatial Connections  Spatial-temporal Learning  Graph Neural Network  Attention Mechanism