Spectral Observation Convolutional Neural Network

This project developed method to analyze collected radiation spectra using advanced, scalable deep learning by combining spectroscopic expertise with high performance computing. Sophisticated deep learning can overcome the weaknesses of existing spectroscopic techniques and enhance the value of difficult measurements. This method was trained, tested, and operated on the International Space Station’s Spaceborne Computer-2 supercomputer, returning zero errors over the course of 100 training hours. This demonstrated performance autonomously in far-edge, low-wattage computing situations and in hazardous radiological environments where interference
can cause errors.