Speaker
Carlos Diez
(Muon Tomography Systems S.L.)
Description
Several applications of scattering muon tomography require the estimation of a limited number of key parameters associated to a given sample. In this presentation we explore the use of the quantiles of the angular and spatial deviation distributions as the input to Deep Neural Networks regressing on the parameters of interest. We provide examples related to the measurement of the position of the electrodes in an electric furnace and also on the estimation of the snow water equivalent (SWE) in snowpacks.
Primary author
Carlos Diez
(Muon Tomography Systems S.L.)
