Swin Resnetswin Transformers for Change Detection in Remote Sensing Images-Reference-Cited by-同舟云学术

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Swin Resnetswin Transformers for Change Detection in Remote Sensing Images

Published:2023-07-16 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Liu Xu¹,Liu Yu¹,Jiao Licheng¹,Li Lingling¹,Liu Fang¹,Zhang Dan¹

Affiliation:

1. Xidian University,International Research Center for Intelligent Perception and Computation, Joint International Research Laboratory of Intelligent Perception and Computation, School of Artificial Intelligence,Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education,Xian,China,710071

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10283256.pdf?arnumber=10283256

Reference11 articles.

1. Segformer: Simple and efficient design for semantic segmentation with transformers;xie;Advances in neural information processing systems,2021

2. Deep residual learning;he;Image Recognition,2015

3. Fully Convolutional Siamese Networks for Change Detection

4. ADS-Net:An Attention-Based deeply supervised network for remote sensing image change detection

5. Deep Learning for Change Detection in Remote Sensing Images: Comprehensive Review and Meta-Analysis

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