A Probabilistic Joint Sparse Regression Model for Semisupervised Hyperspectral Unmixing
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2017.2649418
Abstract: Semisupervised hyperspectral unmixing finds the ratio of spectral library members in the mixture of hyperspectral pixels to find the proportion of pure materials in a natural scene. The two main challenges are noise in observed… read more here.
Keywords: model; sparse regression; hyperspectral unmixing; semisupervised hyperspectral ... See more keywords
Semisupervised hyperspectral imagery classification based on a three-dimensional convolutional adversarial autoencoder model with low sample requirements
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.14.024522
Abstract: Abstract. Although there are many state-of-the-art methods for hyperspectral classification, data deficiency is a problem that should be addressed before popularizing hyperspectral technology. To solve this problem, it is worth exploring methods based on small… read more here.
Keywords: semisupervised hyperspectral; adversarial autoencoder; dimensional convolutional; three dimensional ... See more keywords