Unsupervised change-detection based on convolutional-autoencoder feature extraction-Reference-Cited by-同舟云学术

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Unsupervised change-detection based on convolutional-autoencoder feature extraction

Published:2019-10-07 Issue: Volume: Page:
ISSN:
Container-title:Image and Signal Processing for Remote Sensing XXV
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Author:

Bergamasco Luca,Saha Sudipan,Bovolo Francesca,Bruzzone Lorenzo

Publisher

SPIE

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advances and Challenges in Deep Learning-Based Change Detection for Remote Sensing Images: A Review through Various Learning Paradigms;Remote Sensing;2024-02-25

2. Multiscale Hierarchical Losses to Preserve Hidden-Layer Features for Unsupervised Change Detection;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Unsupervised CD in Satellite Image Time Series by Contrastive Learning and Feature Tracking;IEEE Transactions on Geoscience and Remote Sensing;2024

4. Novel Contrastive Regularized Bipartite Network for Unsupervised Change Detection;2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS);2023-10-31

5. Self-supervised remote sensing image change detection based on high frequency feature and gate attention-guided optimization unit;Journal of Applied Remote Sensing;2023-06-05

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