VAE-AD: Unsupervised Variational Autoencoder for Anomaly Detection in Hyperspectral Images

Nikhil Ojha; Indrajeet Kumar Sinha; Krishna Pratap Singh

doi:10.1007/978-981-99-1648-1_11

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VAE-AD: Unsupervised Variational Autoencoder for Anomaly Detection in Hyperspectral Images

Nikhil Ojha Indrajeet Kumar Sinha Krishna Pratap Singh

Year: 2023 Communications in computer and information science Pages: 126-137 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-99-1648-1_11

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Keywords:

Autoencoder Hyperspectral imaging Anomaly detection Artificial intelligence Pattern recognition (psychology) Computer science Anomaly (physics) Pixel Construct (python library) Representation (politics) Image (mathematics) Computer vision Artificial neural network Physics

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Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Chemical Sensor Technologies

Physical Sciences → Engineering → Biomedical Engineering

VAE-AD: Unsupervised Variational Autoencoder for Anomaly Detection in Hyperspectral Images

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