Quantum Convolutional Neural Networks for Image Classification: Perspectives and Challenges

Fabio Napoli, Lelio Campanile, Giovanni De Gregorio, Giovanni De Gregorio, Stefano Marrone

2025

Abstract

Quantum Computing is becoming a central point of discussion in both academic and industrial communities. Quantum Machine Learning is one of the most promising subfields of this technology, in particular for image classification. In this paper, the model of Quantum Convolutional Neural Networks and some related implementations are explored in their potential for a non-trivial task of image classification. The paper presents some experimentations and discusses the limitations and the strengths of these approaches when compared with classical Convolutional Neural Networks. Furthermore, an analysis of the impact of the noise level on the quality of the classification task has been performed. This paper reports a substantial equivalence of the perfomance of the model with respect the level of noise.

Paper Citation

in Harvard Style

Napoli F., Campanile L., De Gregorio G. and Marrone S. (2025). Quantum Convolutional Neural Networks for Image Classification: Perspectives and Challenges. In Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - Volume 1: AI4EIoT; ISBN 978-989-758-750-4, SciTePress, pages 509-516. DOI: 10.5220/0013521500003944

in Bibtex Style

@conference{ai4eiot25,
author={Fabio Napoli and Lelio Campanile and Giovanni De Gregorio and Stefano Marrone},
title={Quantum Convolutional Neural Networks for Image Classification: Perspectives and Challenges},
booktitle={Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - Volume 1: AI4EIoT},
year={2025},
pages={509-516},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013521500003944},
isbn={978-989-758-750-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - Volume 1: AI4EIoT
TI - Quantum Convolutional Neural Networks for Image Classification: Perspectives and Challenges
SN - 978-989-758-750-4
AU - Napoli F.
AU - Campanile L.
AU - De Gregorio G.
AU - Marrone S.
PY - 2025
SP - 509
EP - 516
DO - 10.5220/0013521500003944
PB - SciTePress