Context-aware lightweight remote-sensing image super-resolution network
In recent years, remote-sensing image super-resolution (RSISR) methods based on convolutional neural networks (CNNs) have achieved significant progress. However, the limited receptive field of the convolutional kernel in CNNs hinders the network's ability to effectively capture long-range featu...
Main Authors: | Guangwen Peng, Minghong Xie, Liuyang Fang |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2023-06-01
|
Series: | Frontiers in Neurorobotics |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fnbot.2023.1220166/full |
Similar Items
-
A lightweight distillation CNN-transformer architecture for remote sensing image super-resolution
by: Yu Wang, et al.
Published: (2023-12-01) -
Lightweight Super-Resolution with Self-Calibrated Convolution for Panoramic Videos
by: Fanjie Shang, et al.
Published: (2022-12-01) -
Enhanced Single Image Super Resolution Method Using Lightweight Multi-Scale Channel Dense Network
by: Yooho Lee, et al.
Published: (2021-05-01) -
A Lightweight Feature Distillation and Enhancement Network for Super-Resolution Remote Sensing Images
by: Feng Gao, et al.
Published: (2023-04-01) -
Super-Resolution Network for Remote Sensing Images via Preclassification and Deep–Shallow Features Fusion
by: Xiuchao Yue, et al.
Published: (2022-02-01)