We present a novel Dual Window-based Self-Attention (DWSA) module, comprising distributed global attention and concentrated local attention, for remote sensing ...
Transformers have recently gained significant attention in low-level vision tasks, particularly for remote sensing image super-resolution (RSISR).
Aug 2, 2024 · Enhanced Window-Based Self-Attention with Global and Multi-Scale Representations for Remote Sensing Image Super-Resolution. Remote Sensing.
Apr 18, 2024 · This study proposes a Multi-Scale Sliding Window Attention Generation Adversarial Network (MSWAGAN) , which combines the advantages of ...
An attention-based multilevel feature fusion network (AMFFN) to enhance the resolution of RSIs and is expanded to the field of natural image super-resolution ( ...
This paper presents an effective method to grasp the global and local image hierarchies by systematically exploring the cross-scale correlation.
Super-resolution (SR) aims to increase the image resolution while providing finer spatial details, which perfectly remedies the weakness of satellite images.
We proposed ST-MDAMNet based on Swin Transformer and combined with the multi-dimensional attention mechanism.
Sep 10, 2024 · This paper proposes a new lightweight multi-scale feature fusion network model based on two-way complementary convolutional and Transformer.
This repository provides an exhaustive overview of deep learning techniques specifically tailored for satellite and aerial image processing.