Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

• Main Authors: Tarano, Ana Maria, Close, Sigrid, Gee, Jonathan, Mathias, Donovan, Wheeler, Lorien
• Format: Other/Unknown Material
• Language: unknown
• Published: 2019
• Subjects: Astronomy; Tagish; Tagish Lake
• Online Access: http://hdl.handle.net/2060/20200000439

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs ass...