Semisupervised Spectral Learning With Generative Adversarial Network for Hyperspectral Anomaly Detection
IEEE Transactions on Geoscience and Remote Sensing(2020)
摘要
Limited by the anomalous spectral vectors in unlabeled hyperspectral images (HSIs), anomaly detection methods based on background distribution estimation often suffer from the contamination of anomalies, which decreases the estimation accuracy and, thus, weakens the detection performance. To address this problem, we proposed a novel semisupervised spectral learning (SSL) for the hyperspectral anom...
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关键词
Anomaly detection,Hyperspectral imaging,Gallium nitride,Training,Feature extraction,Generative adversarial networks
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