Abstract Synthetic Aperture Radar (SAR), with its coherent imaging mechanism, has the
unique advantage of all-day and all-weather imaging. As a typical and important topic …

With the development of deep learning (DL) and synthetic aperture radar (SAR) imaging
techniques, SAR automatic target recognition has come to a breakthrough. Numerous …

Convolutional neural network (CNN)-based methods have been successfully applied to
SAR target detection. Different from prevalently used detection approaches with rectangle …

Target detection and recognition are popular issues in the field of high-resolution Synthetic
Aperture Radar (SAR). As a typical target, aircraft detection and identification has certain …

Aircraft detection in synthetic aperture radar (SAR) images is still a challenging research
task because of the insufficient public data, the difficulty of multiscale target detection, and …

Automatic target recognition of synthetic aperture radar (SAR) images has been a vital issue
in recent studies. The recognition methods can be divided into two main types: traditional …

Aircraft detection in synthetic aperture radar (SAR) images plays a significant role in
dynamic monitoring and national security. Previous methods have difficulty in obtaining the …

Although deep learning techniques have achieved noticeable success in aircraft detection,
the scale heterogeneity, position difference, complex background interference, and speckle …

Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challenging task in SAR
Automatic Target Recognition (SAR ATR) areas due to aircraft's extremely discrete …

Aircraft classification in synthetic aperture radar (SAR) images plays a considerable role in
global region management and surveillance. Recently, deep learning has been applied to …