From the 1 of 4 linked papers with an AI index.
4 papers
CoRE-UIR: Prior-guided common and residual experts for efficient all-in-one remote sensing image restoration
Zaiyan Zhang, Qiangqiang Yuan, Jie Li +5
The paper introduces CoRE-UIR, a prior‑guided framework that separates restoration into a common dense expert and low‑rank residual experts to efficiently handle multiple degradati…
Spiking Meets Attention: Efficient Remote Sensing Image Super-Resolution with Attention Spiking Neural Networks
Yi Xiao, Qiangqiang Yuan, Kui Jiang +5
Spiking neural networks (SNNs) are emerging as a promising alternative to traditional artificial neural networks (ANNs), offering biological plausibility and energy efficiency. Des…
A Single-Frame and Multi-Frame Cascaded Image Super-Resolution Method
Jing Sun, Qiangqiang Yuan, Huanfeng Shen +2
The objective of image super-resolution is to reconstruct a high-resolution (HR) image with the prior knowledge from one or several low-resolution (LR) images. However, in the real…
Super-Resolution for Remote Sensing Imagery via the Coupling of a Variational Model and Deep Learning
Jing Sun, Huanfeng Shen, Qiangqiang Yuan +1
Image super-resolution (SR) is an effective way to enhance the spatial resolution and detail information of remote sensing images, to obtain a superior visual quality. As SR is sev…