MsIFT: Multi-Source Image Fusion Transformer
Multi-source image fusion is very important for improving image representation ability since its essence relies on the complementarity between multi-source information. However, feature-level image fusion methods based on the convolution neural network are impacted by the spatial misalignment betwee...
Main Authors: | Xin Zhang, Hangzhi Jiang, Nuo Xu, Lei Ni, Chunlei Huo, Chunhong Pan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-08-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/14/16/4062 |
Similar Items
-
TR-MISR: Multiimage Super-Resolution Based on Feature Fusion With Transformers
by: Tai An, et al.
Published: (2022-01-01) -
GFFNet: Global Feature Fusion Network for Semantic Segmentation of Large-Scale Remote Sensing Images
by: Yong Cao, et al.
Published: (2024-01-01) -
Study on Multi-source Data Fusion Framework Based on Graph
by: KUANG Guang-sheng, GUO Yan, YU Xiao-ming, LIU Yue, CHENG Xue-qi
Published: (2021-11-01) -
Multitask Learning for Ship Detection From Synthetic Aperture Radar Images
by: Xin Zhang, et al.
Published: (2021-01-01) -
Infrasound Source Localization of Distributed Stations Using Sparse Bayesian Learning and Bayesian Information Fusion
by: Ran Wang, et al.
Published: (2022-07-01)