Image Regression With Structure Cycle Consistency for Heterogeneous Change Detection

Change detection (CD) between heterogeneous images is an increasingly interesting topic in remote sensing. The different imaging mechanisms lead to the failure of homogeneous CD methods on heterogeneous images. To address this challenge, we propose a structure cycle consistency-based image regressio...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transaction on neural networks and learning systems Ročník 35; číslo 2; s. 1613 - 1627
Hlavní autoři:	Sun, Yuli, Lei, Lin, Guan, Dongdong, Wu, Junzheng, Kuang, Gangyao, Liu, Li
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.02.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptive graph (AG) Change detection Change detection algorithms Consistency cycle consistency Feature extraction Fractals heterogeneous image regression Learning systems multimodal Radar polarimetry Regression Regularization Remote sensing Source code Training Transformations (mathematics) unsupervised change detection (CD)
ISSN:	2162-237X, 2162-2388, 2162-2388
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!