With the significant advancement of sensor and communication technology and the reliable
application of obstacle detection techniques and algorithms, automated driving is becoming …

Integrating information collected by different types of sensors observing the same or related
phenomenon can lead to more accurate and robust decision making. The purpose of this …

Synthetic aperture radar automatic target recognition (SAR-ATR) has made great progress
in recent years. Most of the established recognition methods are supervised, which have …

SAR-optical images from different sensors can provide consistent information for scene
classification. However, the utilization of unlabeled SAR-optical images in deep learning …

Recently, remote sensing community has seen a surge in the use of multimodal data for
different tasks such as land cover classification, change detection and many more. However …

Due to the different imaging modes of SAR images and optical images, traditional image
fusion methods are no longer suitable for the fusion of the two types of images. Fused …

In recent years, target recognition technology for synthetic aperture radar (SAR) images has
witnessed significant advancements, particularly with the development of convolutional …

Using satellite remote sensing has become a mainstream approach for extracting crop
spatial distribution. Making edges finer is a challenge, while simultaneously extracting crop …

In the Information Age, the widespread usage of blackbox algorithms makes it difficult to
understand how data is used. The practice of sensor fusion to achieve results is widespread …

Synthetic aperture radar (SAR) and optical images possess complementary strengths,
offering rich spatial and spectral information. The intelligent classification of features through …