RANet: Relationship Attention for Hyperspectral Anomaly Detection

RANet: Relationship Attention for Hyperspectral Anomaly Detection

Hyperspectral anomaly detection (HAD) is of great interest for unknown exploration. Existing methods only focus on local similarity, which may show limitations in detection performance. To cope with this problem, we propose a relationship attention-guided unsupervised learning with convolutional aut...

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Bibliographic Details
Main Authors: Yingzhao Shao, Yunsong Li, Li Li, Yuanle Wang, Yuchen Yang, Yueli Ding, Mingming Zhang, Yang Liu, Xiangqiang Gao
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Remote Sensing
Subjects:
anomaly detection
hyperspectral image
graph attention network (GAT)
convolutional autoencoder (CAE)
Online Access:https://www.mdpi.com/2072-4292/15/23/5570

Internet

https://www.mdpi.com/2072-4292/15/23/5570

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