This article presents a comprehensive survey of deep learning applications for object
detection and scene perception in autonomous vehicles. Unlike existing review papers, we …

Multi-scale object detection within Synthetic Aperture Radar (SAR) images has become a
research hotspot in SAR image interpretation. Over the past few years, CNN-based …

The aerial objects tend to distribute with a major variation in the scale and arbitrary
orientations in remote sensing images. To meet such characteristics of the aerial object …

Accurate registration between synthetic aperture radar (SAR) images is the basis for high-
precision geometric correction of SAR images. The feature points extracted by conventional …

Recently, most state-of-the-art object detection systems adopt anchor box mechanism to
simplify the detection model. Neural networks only need to regress the mapping relations …

Recently, the improvement of detection performance always relies on deeper convolutional
layers and complex convolutional structures in remote sensing images, which significantly …

In recent years, object detectors based on convolutional neural networks have been widely
used on remote sensing images. However, the improvement of their detection performance …

Frequent and accurate object detection based on remote sensing images can effectively
monitor dynamic objects on the earth's surface. While the detection transformer (DETR) …

With the continuous development of synthetic aperture radar (SAR) systems,
multipolarization information has been increasingly applied to numerous fields, and …

The deep learning technique has recently led to significant improvement in object detection
accuracy. In many applications, object detection is performed on video data consisting of a …