Change detection in VHR Remote Sensing Images by automatic sample selection and progressive classification-Reference-Cited by-同舟云学术

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Change detection in VHR Remote Sensing Images by automatic sample selection and progressive classification

Published:2023-11-02 Issue:21 Volume:44 Page:6595-6614
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Shen Yuzhen¹²³^ORCID,Yu Yuanhe¹²³^ORCID,Wei Yuchun¹²³,Guo Houcai¹²³,Rui Xudong¹²³

Affiliation:

1. School of Geography, Nanjing Normal University, Nanjing, China

2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China

3. Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2273245

Reference64 articles.

1. Automatic analysis of the difference image for unsupervised change detection

2. A new difference image creation method based on deep neural networks for change detection in remote-sensing images

3. Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

4. Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and $k$-Means Clustering

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