Výsledky vyhledávání - Adaptive spatial–temporal graph convolutional network

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    ST_AGCNT: Traffic Speed Forecasting Based on SpatialTemporal Adaptive Graph Convolutional Network with Transformer Autor Cheng, Rongjun, Liu, Mengxia, Xu, Yuanzi

    ISSN: 2071-1050, 2071-1050
    Vydáno: Basel MDPI AG 01.03.2025
    Vydáno v Sustainability (01.03.2025)
    “… In order to overcome these challenges, a SpatialTemporal Adaptive Graph Convolutional Network with Transformer (ST_AGCNT…”
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    AdpSTGCN: Adaptive spatialtemporal graph convolutional network for traffic forecasting Autor zhang, Xudong, Chen, Xuewen, Tang, Haina, Wu, Yulei, Shen, Hanji, Li, Jun

    ISSN: 0950-7051
    Vydáno: Elsevier B.V 09.10.2024
    Vydáno v Knowledge-based systems (09.10.2024)
    “… To address this challenge, we propose an adaptive spatialtemporal graph convolutional network for traffic forecasting…”
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    An attention-based adaptive spatialtemporal graph convolutional network for long-video ergonomic risk assessment Autor Zhou, Chengju, Zeng, Jiayu, Qiu, Lina, Wang, Shuxi, Liu, Pingzhi, Pan, Jiahui

    ISSN: 0952-1976, 1873-6769
    Vydáno: Elsevier Ltd 01.05.2024
    “…). Among the automatic approaches, algorithms based on graph convolutional networks (GCNs) have shown promising results in ERA using skeleton sequence as input…”
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    Traffic Police 3D Gesture Recognition Based on Spatial-Temporal Fully Adaptive Graph Convolutional Network Autor Fu, Zheng, Chen, Junjie, Jiang, Kun, Wang, Sijia, Wen, Junze, Yang, Mengmeng, Yang, Diange

    ISSN: 1524-9050, 1558-0016
    Vydáno: New York IEEE 01.09.2023
    “… Meanwhile, a fully adaptive spatial-temporal graph convolution network (FA-STGCN) is proposed to recognize the actions with different amplitude and frequencies…”
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    Attention-based spatialtemporal adaptive dual-graph convolutional network for traffic flow forecasting Autor Xia, Dawen, Shen, Bingqi, Geng, Jian, Hu, Yang, Li, Yantao, Li, Huaqing

    ISSN: 0941-0643, 1433-3058
    Vydáno: London Springer London 01.08.2023
    Vydáno v Neural computing & applications (01.08.2023)
    “…–temporal adaptive dual-graph convolutional network (ASTA-DGCN) for TFF in this paper. Specifically, we employ a spatial…”
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    A SpatialTemporal Adaptive Graph Convolutional Network with Multi-Sensor Signals for Tool Wear Prediction Autor Xia, Yu, Zheng, Guangji, Li, Ye, Liu, Hui

    ISSN: 2076-3417, 2076-3417
    Vydáno: Basel MDPI AG 01.02.2025
    Vydáno v Applied sciences (01.02.2025)
    “… To overcome these limitations, a novel spatialtemporal adaptive graph convolutional network (STAGCN…”
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    AFSTGCN: Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network Autor Xiao, Yuteng, Xia, Kaijian, Yin, Hongsheng, Zhang, Yu-Dong, Qian, Zhenjiang, Liu, Zhaoyang, Liang, Yuehan, Li, Xiaodan

    ISSN: 2352-8648, 2468-5925, 2352-8648
    Vydáno: Elsevier B.V 01.04.2024
    Vydáno v Digital communications and networks (01.04.2024)
    “… In this paper, we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network (AFSTGCN). First, to address the problem of the unknown spatial-temporal structure, we construct the Adaptive Fused Spatial-Temporal Graph…”
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    Multi‐stream adaptive spatialtemporal attention graph convolutional network for skeleton‐based action recognition Autor Yu, Lubin, Tian, Lianfang, Du, Qiliang, Bhutto, Jameel Ahmed

    ISSN: 1751-9632, 1751-9640
    Vydáno: Stevenage John Wiley & Sons, Inc 01.03.2022
    Vydáno v IET computer vision (01.03.2022)
    “… Graph convolutional networks (GCNs) generalize convolutional neural networks (CNNs) to non‐Euclidean graphs and achieve significant performance in skeleton…”
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    A novel adaptive spatialtemporal cross-graph convolutional fusion learning network for skeleton-based abnormal gait recognition Autor Wang, Liang, Wu, Xiaoyan, Wu, Bin, Wu, Jianning

    ISSN: 0952-1976
    Vydáno: Elsevier Ltd 15.08.2025
    “… In this study, a novel adaptive spatialtemporal cross-graph convolutional fusion learning network is proposed to accurately recognize skeleton-based abnormal gait patterns…”
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    MAST-GCN: Multi-Scale Adaptive Spatial-Temporal Graph Convolutional Network for EEG-Based Depression Recognition Autor Lu, Haifeng, You, Zhiyang, Guo, Yi, Hu, Xiping

    ISSN: 1949-3045, 1949-3045
    Vydáno: Piscataway IEEE 01.10.2024
    “… In this paper, we propose Multi-scale Adaptive Spatial-Temporal Graph Convolutional Network (MAST-GCN) for mining latent topological structure among EEG channels and capturing discriminative spatio-temporal features…”
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    SAST-GCN: Segmentation Adaptive Spatial Temporal-Graph Convolutional Network for P3-Based Video Target Detection Autor Lu, Runnan, Zeng, Ying, Zhang, Rongkai, Yan, Bin, Tong, Li

    ISSN: 1662-453X, 1662-4548, 1662-453X
    Vydáno: Frontiers Media S.A 02.06.2022
    Vydáno v Frontiers in neuroscience (02.06.2022)
    “… This paper proposes a segmentation adaptive spatial-temporal graph convolutional network (SAST-GCN) for P3-based video target detection…”
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    Spatial-temporal dual-channel adaptive graph convolutional network for remaining useful life prediction with multi-sensor information fusion Autor Zhang, Xingwu, Leng, Zhenjiang, Zhao, Zhibin, Li, Ming, Yu, Dan, Chen, Xuefeng

    ISSN: 1474-0346, 1873-5320
    Vydáno: Elsevier Ltd 01.08.2023
    Vydáno v Advanced engineering informatics (01.08.2023)
    “… To overcome these limitations, a novel graph neural network framework, namely, Spatialtemporal Dual-channel Adaptive Graph Convolutional Network (SDAGCN…”
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    STADGCN: spatialtemporal adaptive dynamic graph convolutional network for traffic flow prediction Autor Shi, Ying, Cui, Wentian, Wang, Ruiqin, Lou, Jungang, Shen, Qing

    ISSN: 0941-0643, 1433-3058
    Vydáno: London Springer London 01.07.2025
    Vydáno v Neural computing & applications (01.07.2025)
    “… In this paper, we propose a novel spatialtemporal adaptive dynamic graph convolutional network for traffic flow prediction…”
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    SSTGCNs: Spectral-Spatial-Temporal Long-Range Dependencies Joint Feature Extraction With Graph Convolutional Networks for Adaptive Change Detection Autor Chang, Zhanyuan, Wei, Yuwen, Lian, Jie, Jin, Mingxiao, Wang, Dong, Li, Xuyang

    ISSN: 1939-1404, 2151-1535
    Vydáno: Piscataway IEEE 2025
    “… To solve the above problems, this article proposes spectral-spatial-temporal long-range dependencies joint feature extraction with graph convolutional networks…”
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    Enhancing aquaculture water quality forecasting using novel adaptive multi-channel spatial-temporal graph convolutional network Autor Xiang, Tianqi, Guo, Xiangyun, Chi, Junjie, Gao, Juan, Zhang, Luwei

    ISSN: 1934-6344, 1934-6352
    Vydáno: Beijing International Journal of Agricultural and Biological Engineering (IJABE) 01.02.2025
    “… To address this challenge, a prediction model was proposed for water quality, namely an adaptive multi-channel temporal graph convolutional network (AMTGCN…”
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    Human Action Recognition Based on Spatial Temporal Adaptive Residual Graph Convolutional Networks with Attention Mechanism Autor Song, Lu, He, Yi, Yuan, Huaqing, Du, Peng

    ISSN: 1934-1768
    Vydáno: Technical Committee on Control Theory, Chinese Association of Automation 28.07.2024
    Vydáno v Chinese Control Conference (28.07.2024)
    “… This may not be suitable for the diversity of action categories. To address this, we propose a spatial-temporal adaptive residual graph convolutional network with an attention mechanism…”
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    A coarse-to-fine adaptive spatialtemporal graph convolution network with residuals for motor imagery decoding from the same limb Autor Zhu, Lei, Yuan, Jie, Huang, Aiai, Zhang, Jianhai

    ISSN: 1746-8094, 1746-8108
    Vydáno: Elsevier Ltd 01.04.2024
    “…–temporal graph convolutional network with residuals approach is proposed to extract spatial…”
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    Adaptive Spatial-Temporal Fusion Graph Convolutional Networks for Traffic Flow Forecasting Autor Li, Senwen, Ge, Liang, Lin, Yongquan, Zeng, Bo

    ISSN: 2161-4407
    Vydáno: IEEE 18.07.2022
    “… It may not accurately reflect the spatial-temporal correlations among nodes. Secondly, only the correlations among nodes adjacent in time or space are considered in each graph convolutional layer…”
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    SpatialTemporal Similarity Fusion Graph Adversarial Convolutional Networks for traffic flow forecasting Autor Wang, Bin, Long, Zhendan, Sheng, Jinfang, Zhong, Qiang

    ISSN: 0016-0032
    Vydáno: Elsevier Inc 01.11.2024
    Vydáno v Journal of the Franklin Institute (01.11.2024)
    “… This paper introduces a novel model, the SpatialTemporal Similarity Fusion Graphs Adversarial Convolutional Networks (STSF-GACN…”
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