COMIC: An unsupervised change detection method for heterogeneous remote sensing images based on copula mixtures and Cycle-Consistent Adversarial Networks-Reference-Cited by-同舟云学术

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COMIC: An unsupervised change detection method for heterogeneous remote sensing images based on copula mixtures and Cycle-Consistent Adversarial Networks

Published:2024-06 Issue: Volume:106 Page:102240
ISSN:1566-2535
Container-title:Information Fusion
language:en
Short-container-title:Information Fusion

Author:

Li Chengxi,Li Gang,Wang Zhuoyue,Wang Xueqian,Varshney Pramod K.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Tsinghua University

Publisher

Elsevier BV

Reference77 articles.

1. MLCA2F: multi-level context attentional feature fusion for COVID-19 lesion segmentation from CT scans;Bakkouri;Signal Image Video Process.,2022

2. BG-3DM2F: bidirectional gated 3D multi-scale feature fusion for Alzheimer's disease diagnosis;Bakkouri;Multimed. Tools Appl.,2022

3. Robust fusion algorithms for unsupervised change detection between multi-band optical images — a comprehensive case study;Ferraris;Inf. Fusion,2020

4. ISNet: towards improving separability for remote sensing image change detection;Cheng;IEEE Trans. Geosci. Remote Sens.,2022

5. Information fusion techniques for change detection from multi-temporal remote sensing images;Du;Inf. Fusion,2013

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