Hypothesized Surface: Sample Return from Hypothesized Surfaces – Sample Site Selection Using Machine Learning

INSTITUTION

Virginia Commonwealth University (VCU)

CLASS

Tungsten Class (2023 – 2024)

STUDENT TEAM

ACADEMIC GUIDANCE

Dr. Preetam Ghosh, Professor and Interim Chair of Computer Science, Department of Computer Science, Virginia Commonwealth University

PROJECT DESCRIPTION

We are creating a CNN model with tensorflow(keras) to help distinguish between different characteristics found on the asteroid. Our model will be able to distinguish between rock, sand dunes, craters, and more in order to determine the best place to sample material. The model will then tell the user if the pictures they added had any good sample spots or not.

This work was created in partial fulfillment of the Virginia Commonwealth University Capstone Course “CMSC 451”. The work is a result of the Psyche Student Collaborations component of NASA’s Psyche Mission (https://psyche.asu.edu). “Psyche: A Journey to a Metal World” [Contract number NNM16AA09C] is part of the NASA Discovery Program mission to solar system targets. Trade names and trademarks of ASU and NASA are used in this work for identification only. Their usage does not constitute an official endorsement, either expressed or implied, by Arizona State University or National Aeronautics and Space Administration. The content is solely the responsibility of the authors and does not necessarily represent the official views of ASU or NASA.