Learning Token-Aligned Representations With Multimodel Transformers for Different-Resolution Change Detection-Reference-Cited by-同舟云学术

Learning Token-Aligned Representations With Multimodel Transformers for Different-Resolution Change Detection

Published:2022 Issue: Volume:60 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:

Liu Mengxi¹^ORCID,Shi Qian¹^ORCID,Li Jianlong¹,Chai Zhuoqun¹

Affiliation:

1. Guangdong Provincial Key Laboratory for Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09864212.pdf?arnumber=9864212

Reference52 articles.

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4. Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery

5. Superpixel-Based Difference Representation Learning for Change Detection in Multispectral Remote Sensing Images

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