Microwave Remote Sensing for Object Detection

Dear Colleagues,

As a method of microwave remote sensing, synthetic aperture radar (SAR) technology has developed rapidly in recent years, while the SAR image processing is developing towards achieving higher resolution, multi polarization and high processing speeds. By focusing on various imaging scenes such as airports, harbors, complicated land regions or sea, the SAR images can cover different objects such as airplanes, ships, vehicles, etc. The question of how to locate and find interesting targets quickly and accurately using these large-scale SAR images is clearly gaining significance. For instance, real-time ship detection methods in SAR images are conducive to marine resource management, search and rescue and so on. In particular, the detection and recognition method based on deep learning promotes the ability of target detection in microwave images.

This Special Issue aims to include studies that cover different object detection methods based on different microwave remote sensors and platforms. Topics may cover anything from the target detection, target recognition under complicated land regions or sea conditions, to more comprehensive targets and scenes. Hence, both conventional detection methods and new deep learning-based object detection methods, such as convolutional neural networks and transformer networks for microwave images, are welcome.

• Target detection and recognition in microwave images/SAR images;
• Deep learning methods for SAR image understanding;
• Transfer learning and few sample learning in SAR images.

Prof. Dr. Guangcai Sun
Dr. Jiang Qian
Dr. Lei Yang
Dr. Jinsong Zhang
Guest Editors

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