Automated Interpretability Scoring of Ground-Based Observations of LEO Objects with Deep Learning

• Published in: 2020 IEEE Aerospace Conference pp. 1 - 7
• Main Authors: Lucas, Jacob, Werth, Michael, Kyono, Trent, Mcquaid, Ian, Fletcher, Justin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2020
• Subjects: Image quality; Knowledge engineering; Low earth orbit satellites; Machine vision; Neural networks; Observatories; Satellites

The Space-object National Imagery Interpretability Rating Scale (SNIIRS) allows human analysts to provide a quantitative score of image quality based on identification of target features. It is naturally difficult to automate this scoring process, not only because the scale is based on identifiable...