Morpheus: A Deep Learning Framework For Pixel-Level Analysis of Astronomical Image Data

Ryan Hausen University of California, Santa Cruz Graduate Student Abstract: Astronomy is on the cusp of a big data revolution. Upcoming telescopes like the Rubin Observatory are going to produce terabytes of data nightly. Data analysis of this scale is beyond the realm of purely human efforts, motivating astronomers to explore applying techniques based on advances in machine learning and computer vision. An essential aspect of astronomical image analysis is source detection and morphological classification