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Exploring the Intrinsic Probability Distribution for Hyperspectral Anomaly Detection
2022
Remote Sensing
In recent years, neural network-based anomaly detection methods have attracted considerable attention in the hyperspectral remote sensing domain due to their powerful reconstruction ability compared with traditional methods. However, actual probability distribution statistics hidden in the latent space are not discovered by exploiting the reconstruction error because the probability distribution of anomalies is not explicitly modeled. To address the issue, we propose a novel probability
doi:10.3390/rs14030441
fatcat:4xhsgzo5v5bytpyiaw7xzqp2pm