Advanced AI-Based Solutions for Visual Inspection: A Systematic Literature Review

Angelo Corallo, Vito Del Vecchio, Alberto Di Prizio

2024

Abstract

Artificial Intelligence (AI)-based solutions, including Machine Learning (ML) and Deep Learning (DL), are ever more implemented in industry for assisting advanced Visual Inspection (VI) systems. They support companies in a more effective identification of product defects, enhancing the performance of humans and avoiding the risks of product incompliance. However, companies often struggle in considering the most appropriate AI-based solutions for VI and for a specific manufacturing domain. Also, an extensive literature study focused on this topic seems to lack. On the basis of a Systematic Literature Review, this paper aims to map the main advanced AI-based VI system solutions (including methods, technologies, techniques, algorithms) thus helping companies in considering the most appropriate solutions for their needs.

Paper Citation

in Harvard Style

Corallo A., Del Vecchio V. and Di Prizio A. (2024). Advanced AI-Based Solutions for Visual Inspection: A Systematic Literature Review. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 656-664. DOI: 10.5220/0012618000003690

in Bibtex Style

@conference{iceis24,
author={Angelo Corallo and Vito Del Vecchio and Alberto Di Prizio},
title={Advanced AI-Based Solutions for Visual Inspection: A Systematic Literature Review},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={656-664},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012618000003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Advanced AI-Based Solutions for Visual Inspection: A Systematic Literature Review
SN - 978-989-758-692-7
AU - Corallo A.
AU - Del Vecchio V.
AU - Di Prizio A.
PY - 2024
SP - 656
EP - 664
DO - 10.5220/0012618000003690
PB - SciTePress