A Multilevel Multimodal Fusion Transformer for Remote Sensing Semantic Segmentation-Reference-Cited by-同舟云学术

A Multilevel Multimodal Fusion Transformer for Remote Sensing Semantic Segmentation

Published:2024 Issue: Volume:62 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Ma Xianping¹^ORCID,Zhang Xiaokang²^ORCID,Pun Man-On¹^ORCID,Liu Ming³

Affiliation:

1. School of Science and Engineering, the Future Network of Intelligence Institute (FNii), The Chinese University of Hong Kong (Shenzhen), Shenzhen, China

2. School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China

3. MizarVision, Shanghai, China

Funder

Guangdong Provincial Key Laboratory of Future Networks of Intelligence

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10458980.pdf?arnumber=10458980

Reference65 articles.

1. Multimodal Change Detection in Remote Sensing Images Using an Unsupervised Pixel Pairwise-Based Markov Random Field Model

2. Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images

3. More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

4. DKDFN: Domain Knowledge-Guided deep collaborative fusion network for multimodal unitemporal remote sensing land cover classification

5. Road Extraction in Mountainous Regions from High-Resolution Images Based on DSDNet and Terrain Optimization

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