RSCaMa: Remote Sensing Image Change Captioning With State Space Model-Reference-Cited by-同舟云学术

RSCaMa: Remote Sensing Image Change Captioning With State Space Model

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Liu Chenyang¹^ORCID,Chen Keyan²^ORCID,Chen Bowen²^ORCID,Zhang Haotian²^ORCID,Zou Zhengxia²^ORCID,Shi Zhenwei²^ORCID

Affiliation:

1. Image Processing Center, School of Astronautics, the State Key Laboratory of Virtual Reality Technology and Systems, and Shen Yuan Honors College, Beihang University, Beijing, China

2. Shanghai Artificial Intelligence Laboratory, Shanghai, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Beijing Natural Science Foundation

Fundamental Research Funds for Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10537177.pdf?arnumber=10537177

Reference21 articles.

1. BiFA: Remote Sensing Image Change Detection With Bitemporal Feature Alignment

2. RSPrompter: Learning to prompt for remote sensing instance segmentation based on visual foundation model;Chen;arXiv:2306.16269,2023

3. Advances and Challenges in Deep Learning-Based Change Detection for Remote Sensing Images: A Review through Various Learning Paradigms

4. Change Captioning: A New Paradigm for Multitemporal Remote Sensing Image Analysis

5. Remote Sensing Image Change Captioning With Dual-Branch Transformers: A New Method and a Large Scale Dataset

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