Robust multi-stage progressive autoencoder for hyperspectral anomaly detection

Robust multi-stage progressive autoencoder for hyperspectral anomaly detection

Recently, Autoencoders (AEs) have demonstrated remarkable performance in the field of hyperspectral anomaly detection, owing to their powerful capability in handling high-dimensional data. However, they often overlook the inherent global distribution characteristics and long-range dependencies in hy...

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Bibliographic Details
Main Authors:	Qing Guo, Yi Cen, Lifu Zhang, Yan Zhang, Shunshi Hu, Xue Liu
Format:	Article
Language:	English
Published:	Elsevier 2024-11-01
Series:	International Journal of Applied Earth Observations and Geoinformation
Subjects:	Anomaly detection autoencoder (AE) hyperspectral image (HSI) Multi-scale feature fusion Multi-stage learning
Online Access:	http://www.sciencedirect.com/science/article/pii/S1569843224005569
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