4 papers
Understanding Deep Learning using Topological Dynamical Systems, Index Theory, and Homology
Bill Basener
In this paper we investigate Deep Learning Models using topological dynamical systems, index theory, and computational homology. These mathematical machinery was invented initially…
Classifying Crop Types using Gaussian Bayesian Models and Neural Networks on GHISACONUS USGS data from NASA Hyperspectral Satellite Imagery
Bill Basener
Hyperspectral Imagining is a type of digital imaging in which each pixel contains typically hundreds of wavelengths of light providing spectroscopic information about the materials…
Deep Learning of Radiative Atmospheric Transfer with an Autoencoder
Abigail Basener, Bill Basener
As electro-optical energy from the sun propagates through the atmosphere it is affected by radiative transfer effects including absorption, emission, and scattering. Modeling these…
Neural Network Learning of Chemical Bond Representations in Spectral Indices and Features
Bill Basener
In this paper we investigate neural networks for classification in hyperspectral imaging with a focus on connecting the architecture of the network with the physics of the sensing…