Recent developments in intelligent robot systems, especially autonomous vehicles, put
forward higher requirements for safety and comfort. Road conditions are crucial factors …

Pansharpening (which stands for panchromatic (PAN) sharpening) involves the fusion
between a multispectral (MS) image with a higher spectral content than a fine spatial …

Existing deep-learning-based pan-sharpening strategies mainly involve the fusion of
panchromatic and multispectral (MS) information at both the pixel and feature levels. In this …

Training and deploying the large language models requires a large mount of computational
resource because the language models contain billions of parameters and the text has …

Large language models have made significant progress in the past few years. However,
they are either generic {\it or} field specific, splitting the community into different groups. In …

Diffusion models are getting popular in generative image and video synthesis. However,
due to the diffusion process, they require a large number of steps to converge. To tackle this …

Blind pansharpening addresses the problem of generating a high spatial-resolution multi-
spectral (HRMS) image given a low spatial-resolution multi-spectral (LRMS) image with the …

Images captured through glass are usually contaminated by reflections, and the removal of
them from images is a challenging task. Since the primary concern on photos is face, the …

Activation functions are essential components of neural networks. In this paper, we introduce
a new activation function called the Truncated and Signed Square Root (TSSR) function …

Although there are many iterative solvers for total variation models, few attention has been
paid on the fast and effective approximation to their optimal solutions. In this paper, we …