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2022 AAAI AAAI 2022

Unsupervised Identification of Materials with Hyperspectral Images

Abstract

Abstract We introduce a novel technique to identify three spectra representing the three primary materials in a hyperspectral image of a scene. We accomplish this using a modified autoencoder. Further research will be conducted to verify the accuracy of these spectra.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Computer Vision

Authors

Mira Welner

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Learning Types > Unsupervised Learning Deep Learning > Architectures > Autoencoders Computer Vision > Processing > Image Processing Deep Learning > Learning Types > Unsupervised Learning

Keywords

unsupervised learning spectral analysis hyperspectral imaging material identification
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