Deep learning has emerged as a powerful tool in various domains, revolutionising machine
learning research. However, one persistent challenge is the scarcity of labelled training …

Spectral super-resolution (sSR) is a very important technique to obtain hyperspectral images
from only RGB images, which can effectively overcome the high acquisition cost and low …

Recently, convolutional networks have achieved remarkable development in remote
sensing image (RSI) super-resolution (SR) by minimizing the regression objectives, eg, MSE …

Optical-flow-based and kernel-based approaches have been extensively explored for
temporal compensation in satellite Video Super-Resolution (VSR). However, these …

Transformer-based method has demonstrated promising performance in image super-
resolution tasks, due to its long-range and global aggregation capability. However, the …

General-purpose foundation models have led to recent breakthroughs in artificial
intelligence (AI). In remote sensing, self-supervised learning (SSL) and masked image …

In recent years, underwater image enhancement and restoration technologies have become
increasingly important in order to optimize the efficiency of maritime operations and promote …

Mixed noise pollution in HSI severely disturbs subsequent interpretations and applications.
In this technical review, we first give the noise analysis in different noisy HSIs and conclude …

Recent efforts have witnessed remarkable progress in satellite video super-resolution
(SVSR). However, most SVSR methods usually assume the degradation is fixed and known …

Due to the extremely limited prior knowledge, machinery fault diagnosis under varying
working conditions with limited annotation data is a very challenging task in practical …