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Authors: Angelo Corallo ; Vito Del Vecchio and Alberto Di Prizio

Affiliation: Department of Innovation Engineering, University of Salento, Lecce, Italy

Keyword(s): Visual Inspection, Artificial Intelligence, Machine Learning, Deep Learning, Manufacturing, Industry.

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
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; ISSN 2184-4992, SciTePress, pages 656-664. DOI: 10.5220/0012618000003690

@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},
issn={2184-4992},
}

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
IS - 2184-4992
AU - Corallo, A.
AU - Del Vecchio, V.
AU - Di Prizio, A.
PY - 2024
SP - 656
EP - 664
DO - 10.5220/0012618000003690
PB - SciTePress