Date of Award

Spring 5-20-2023

Document Type

Honors Project

University Scholars Director

Dr. Christine Chaney

First Advisor/Committee Member

Dr. Lisa Goodhew

Second Advisor/Committee Member

Dr. John Lindberg

Keywords

astronomy, deep neural networks, artificial intelligence, machine learning, classification

Abstract

As the quantity of astronomical data available continues to exceed the resources available for analysis, recent advances in artificial intelligence encourage the development of automated classification tools. This paper lays out a framework for constructing a deep neural network capable of classifying individual astronomical images by describing techniques to extract and label these objects from large images.

Comments

A project submitted in partial fulfillment of the requirements of the University Scholars Honors Program.

Appendix C - NGC Catalog.csv (118 kB)
Appendix C - NGC Catalog

Appendix D - HD Catalog.csv (69 kB)
Appendix D - HD Catalog

Appendix E - IC Catalog.csv (87 kB)
Appendix E - IC Catalog

Copyright Status

http://rightsstatements.org/vocab/InC-EDU/1.0/

Additional Rights Information

Copyright held by author.

Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS
 
Copyright Status

This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. In addition, no permission is required from the rights-holder(s) for educational uses. For other uses, you need to obtain permission from the rights-holder(s).