Weighted residual network for SAR automatic target recognition with data augmentation.

Journal: Frontiers in neurorobotics
Published Date:

Abstract

INTRODUCTION: Decades of research have been dedicated to overcoming the obstacles inherent in synthetic aperture radar (SAR) automatic target recognition (ATR). The rise of deep learning technologies has brought a wave of new possibilities, demonstrating significant progress in the field. However, challenges like the susceptibility of SAR images to noise, the requirement for large-scale training datasets, and the often protracted duration of model training still persist.

Authors

  • Junyu Li
    School of Electrical and Mechanical Engineering, Hefei Technology College, Hefei, China.
  • Cheng Peng
    School of Electrical and Mechanical Engineering, Hefei Technology College, Hefei, China.

Keywords

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