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Seismic Random Noise Suppression Model Based on Downsampling and Superresolution 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 14
作者:  Fang, Ziyi;  Lin, Hongbo;  Sun, Fuyao;  Song, Xue;  Zhang, Chao;  Wang, Bo
收藏  |  浏览/下载:26/0  |  提交时间:2023/11/17
Noise reduction  Superresolution  Image restoration  Generators  Data models  Complexity theory  Signal resolution  Seismic exploration  seismic random noise  seismic signal denoising  superresolution (SR)  
Context-Aware Dynamic Feature Extraction for 3D Object Detection in Point Clouds 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 页码: 13
作者:  Tian, Yonglin;  Huang, Lichao;  Yu, Hui;  Wu, Xiangbin;  Li, Xuesong;  Wang, Kunfeng;  Wang, Zilei;  Wang, Fei-Yue
收藏  |  浏览/下载:207/0  |  提交时间:2022/01/27
Three-dimensional displays  Feature extraction  Convolution  Proposals  Kernel  Laser radar  Semantics  Point clouds  3D detection  dynamic network  context features  
Multi-object tracking with hard-soft attention network and group-based cost minimization 期刊论文
NEUROCOMPUTING, 2021, 卷号: 447, 页码: 80-91
作者:  Liu, Yating;  Li, Xuesong;  Bai, Tianxiang;  Wang, Kunfeng;  Wang, Fei-Yue
Adobe PDF(2352Kb)  |  收藏  |  浏览/下载:333/83  |  提交时间:2021/08/15
Multi-object tracking  Attention mechanism  Unary and binary costs  Appearance-motion affinity  
Frame-GAN: Increasing the frame rate of gait videos with generative adversarial networks 期刊论文
NEUROCOMPUTING, 2020, 卷号: 380, 页码: 95-104
作者:  Xue, Wei;  Ai, Hong;  Sun, Tianyu;  Song, Chunfeng;  Huang, Yan;  Wang, Liang
收藏  |  浏览/下载:295/0  |  提交时间:2020/03/30
Gait recognition  Generative adversarial networks  Metric learning  Deep learning  
Progress and Outlook of Visual Tracking: Bibliographic Analysis and Perspective 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 184581-184598
作者:  Liu, Yating;  Wang, Kunfeng;  Li, Xuesong;  Bai, Tianxiang;  Wang, Fei-Yue
Adobe PDF(4276Kb)  |  收藏  |  浏览/下载:209/33  |  提交时间:2020/03/30
Visual tracking  bibliographic analysis  collaboration patterns  research hotspots  parallel vision