18 citations · 31 across the 7 of their papers we have counts for
8 papers
Superpixel-based and Spatially-regularized Diffusion Learning for Unsupervised Hyperspectral Image Clustering
Kangning Cui, Ruoning Li, Sam L. Polk +5
Hyperspectral images (HSIs) provide exceptional spatial and spectral resolution of a scene, crucial for various remote sensing applications. However, the high dimensionality, prese…
Unsupervised Spatial-spectral Hyperspectral Image Reconstruction and Clustering with Diffusion Geometry
Kangning Cui, Ruoning Li, Sam L. Polk +3
Hyperspectral images, which store a hundred or more spectral bands of reflectance, have become an important data source in natural and social sciences. Hyperspectral images are oft…
Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering
Sam L. Polk, Aland H. Y. Chan, Kangning Cui +3
Ash dieback (Hymenoscyphus fraxineus) is an introduced fungal disease that is causing the widespread death of ash trees across Europe. Remote sensing hyperspectral images encode ri…
Active Diffusion and VCA-Assisted Image Segmentation of Hyperspectral Images
Sam L. Polk, Kangning Cui, Robert J. Plemmons +1
Hyperspectral images encode rich structure that can be exploited for material discrimination by machine learning algorithms. This article introduces the Active Diffusion and VCA-As…
Unsupervised Diffusion and Volume Maximization-Based Clustering of Hyperspectral Images
Sam L. Polk, Kangning Cui, Aland H. Y. Chan +3
Hyperspectral images taken from aircraft or satellites contain information from hundreds of spectral bands, within which lie latent lower-dimensional structures that can be exploit…
Multiscale Clustering of Hyperspectral Images Through Spectral-Spatial Diffusion Geometry
Sam L. Polk, James M. Murphy
Clustering algorithms partition a dataset into groups of similar points. The primary contribution of this article is the Multiscale Spatially-Regularized Diffusion Learning (M-SRDL…
A Multiscale Environment for Learning by Diffusion
James M. Murphy, Sam L. Polk
Clustering algorithms partition a dataset into groups of similar points. The clustering problem is very general, and different partitions of the same dataset could be considered co…
The Nonuniversality of Wealth Distribution Tails Near Wealth Condensation Criticality
Sam L. Polk, Bruce M. Boghosian
In this work, we modify the affine wealth model of wealth distributions to examine the effects of nonconstant redistribution on the very wealthy. Previous studies of this model, re…