The Qinghai–Tibet Plateau is one of the regions with the highest snow accumulation in
China. Although the Fengyun-4A (FY4A) satellite is capable of monitoring snow-covered …

Low-resolution text images are very commonplace in real life and their information is hard to
be extracted by using existing text recognition methods only. Although this problem can be …

Scene understanding is an important area in robotics and autonomous driving. To
accomplish these tasks, the 3D structures in the scene have to be inferred to know what the …

Super-resolution semantic segmentation (SRSS) is a technique that aims to obtain high-
resolution semantic segmentation results based on resolution-reduced input images. SRSS …

Recently, the importance of semantic segmentation research for scene understanding in
frontal viewing camera images of autonomous vehicles has increased. The existing state-of …

In the realm of infrared and visible scene parsing, satisfactory performance has been
achieved by leveraging the complementary nature of infrared and visible imaging …

Low resolution is a major factor that negatively impacts the accuracy of remote sensing (RS)
interpretation. High-quality super-resolution reconstruction (SRR) can help alleviate this …

Super-resolution (SR) algorithms have been broadly applied to improve the visual quality of
images. However, the unstable SR results and the difficulty of collecting high-resolution (HR) …

The resolution of the image has an important impact on the accuracy of segmentation.
Integrating super-resolution (SR) techniques in the semantic segmentation of remote …

Super-resolution, which aims to reconstruct high-resolution (HR) images from low-resolution
(LR) images, has drawn considerable attention and has been intensively studied in …