Astronomical Images Quality Assessment with Automated Machine Learning

Olivier Parisot; Pierrick Bruneau; Patrik Hitzelberger

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Astronomical Images Quality Assessment with Automated Machine Learning

Topics: Deep Learning; Information Quality

In Proceedings of the 12th International Conference on Data Science, Technology and Applications DATA - Volume 1, 279-286, 2023 , Rome, Italy

Authors: Olivier Parisot ; Pierrick Bruneau and Patrik Hitzelberger

Affiliation: Luxembourg Institute of Science and Technology (LIST), 5 Avenue des Hauts-Fourneaux, 4362 Esch-sur-Alzette, Luxembourg

Keyword(s): Astronomical Images, Image Quality Assessment, Automated Machine Learning.

Abstract: Electronically Assisted Astronomy consists in capturing deep sky images with a digital camera coupled to a telescope to display views of celestial objects that would have been invisible through direct observation. This practice generates a large quantity of data, which may then be enhanced with dedicated image editing software after observation sessions. In this study, we show how Image Quality Assessment can be useful for automatically rating astronomical images, and we also develop a dedicated model by using Automated Machine Learning.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 13.59.122.162

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Parisot, O.; Bruneau, P. and Hitzelberger, P. (2023). Astronomical Images Quality Assessment with Automated Machine Learning. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-664-4; ISSN 2184-285X, SciTePress, pages 279-286. DOI: 10.5220/0012073800003541

@conference{data23,
author={Olivier Parisot. and Pierrick Bruneau. and Patrik Hitzelberger.},
title={Astronomical Images Quality Assessment with Automated Machine Learning},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA},
year={2023},
pages={279-286},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012073800003541},
isbn={978-989-758-664-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA
TI - Astronomical Images Quality Assessment with Automated Machine Learning
SN - 978-989-758-664-4
IS - 2184-285X
AU - Parisot, O.
AU - Bruneau, P.
AU - Hitzelberger, P.
PY - 2023
SP - 279
EP - 286
DO - 10.5220/0012073800003541
PB - SciTePress