A Novel Fully Convolutional Auto-Encoder Based on Dual Clustering and Latent Feature Adversarial Consistency for Hyperspectral Anomaly Detection.
Rui ZhaoZhiwei YangXiangchao MengFeng ShaoPublished in: Remote. Sens. (2024)
Keyphrases
- anomaly detection
- hyperspectral
- hyperspectral images
- remote sensing
- multispectral
- intrusion detection
- infrared
- hyperspectral data
- hyperspectral imagery
- detecting anomalies
- hyperspectral remote sensing
- anomalous behavior
- target detection
- network traffic
- network intrusion detection
- unsupervised learning
- image data
- network anomaly detection
- one class support vector machines
- clustering algorithm
- change detection
- satellite images
- intrusion detection system
- k means
- information content
- self organizing maps
- bit rate
- feature vectors
- detect anomalies
- cluster analysis
- data sets
- clustering method
- feature space
- pattern recognition
- feature extraction
- neural network