MS-Former: Memory-Supported Transformer for Weakly Supervised Change Detection With Patch-Level Annotations-Reference-Cited by-同舟云学术

MS-Former: Memory-Supported Transformer for Weakly Supervised Change Detection With Patch-Level Annotations

Published:2024 Issue: Volume:62 Page:1-13
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Li Zhenglai¹^ORCID,Tang Chang¹^ORCID,Liu Xinwang²^ORCID,Li Changdong³,Li Xianju¹^ORCID,Zhang Wei⁴^ORCID

Affiliation:

1. School of Computer, China University of Geosciences, Wuhan, China

2. School of Computer, National University of Defense Technology, Changsha, China

3. Faculty of Engineering, China University of Geosciences, Wuhan, China

4. Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center, National Supercomputing Center in Jinan, Shandong Academy of Sciences, Qilu University of Technology, Jinan, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10534838.pdf?arnumber=10534838

Reference60 articles.

1. ChangeMask: Deep multi-task encoder-transformer-decoder architecture for semantic change detection

2. An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support

3. A Spatial-Temporal Attention-Based Method and a New Dataset for Remote Sensing Image Change Detection

4. Detecting building changes with off-nadir aerial images

5. A transformer-based Siamese network and an open optical dataset for semantic change detection of remote sensing images