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  • Multiscale Feature Learning Based on Deep Pyramid Residual Shrinking . . .
    In this article, a deep pyramid residual shrinking network (DPRSNet) for radar target detection is proposed First, the pyramid shrinking module is designed to fully mine the discriminative shallow spatial feature information covered in the multiscale space from low signal-noise ratio radar echoes
  • Multiscale Feature Learning Based on Deep Pyramid . . .
    Multiscale Feature Learning Based on Deep Pyramid Residual Shrinking Network for Radar Target Detection,IEEE Transactions on Aerospace and Electronic Systems - X-MOL
  • Multiscale Feature Learning Based on Deep Pyramid Residual Shrinking . . .
    Multiscale Feature Learning Based on Deep Pyramid Residual Shrinking Network for Radar Target Detection IEEE Trans Aerospace and Electronic Systems, 61 (2):3544-3563, April 2025 [doi]
  • Multiscale Feature Learning Based on Deep Pyramid . . .
    Article "Multiscale Feature Learning Based on Deep Pyramid Residual Shrinking Network for Radar Target Detection" Detailed information of the J-GLOBAL is an information service managed by the Japan Science and Technology Agency (hereinafter referred to as "JST")
  • Boyu Wang - Semantic Scholar
    Semantic Scholar profile for Boyu Wang, with 2 scientific research papers
  • lt;br gt;基于深度金字塔残差收缩网络的多尺度特征学习,IEEE . . .
    Our official English website, www x-mol net, welcomes your feedback! (Note: you will need to create a separate account there ) 基于深度金字塔残差收缩网络的多尺度特征学习 IEEE Transactions on Aerospace and Electronic Systems ( IF5 1 ) Pub Date : 2024-10-30, DOI: 10 1109 taes 2024 3488675 Boyu Wang, Gongjian Zhou "点击查看英文标题和摘要" 更新日期：2024-10-30
  • Gongjian Zhou | ScienceDirect
    In this paper, a complex pseudo-spectrum (CPS) method is proposed for VF-TBD to improve the performance of weak target detection, based on the utilization of phase information during energy integration
  • ORCID
    Multiscale Feature Learning Based on Deep Pyramid Residual Shrinking Network for Radar Target Detection IEEE Transactions on Aerospace and Electronic Systems 2025-04 | Journal article : Boyu Wang; Gongjian Zhou
  • レーダターゲット検出のための深層ピラミッド残差縮小 . . .
    Multiscale Feature Learning Based on Deep Pyramid Residual Shrinking Network for Radar Target Detection 出版者サイト 複写サービスで全文入手 高度な検索・分析はJDreamⅢで 著者 (2件)： Wang Boyu
  • Deep-Residual-Shrinkage-Networks 深度残差收缩网络
    This paper develops new deep learning methods, namely, deep residual shrinkage networks, to improve the feature learning ability from highly noised vibration signals and achieve a high fault diagnosing accuracy





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