This article aims to investigate how circuit-based hybrid quantum convolutional neural
networks (QCNNs) can be successfully employed as image classifiers in the context of …

The work explores the integration of quantum computing into logistics and supply chain
management, emphasising its potential for use in complex optimisation problems. The …

Quantum enhanced machine learning: an overview Page 1 Quantum enhanced machine
learning: an overview Pavlo V. Zahorodkoa, Yevhenii O. Modlod, Olga O. Kalinichenkoa …

Quantum computing is a speedily emerging area that applies quantum mechanics
properties to solve complex problems that are difficult for classical computing. Machine …

Variational Quantum Algorithms (VQA) are promising to demonstrate quantum advantages
on near-term devices. Designing ansatz, a variational circuit with parameterized gates, is of …

Abstract Machine learning is now widely used almost everywhere, primarily for forecasting.
In the broadest sense, the machine learning objective may be summarized as an …

This article aims to explore the potential of current approaches for quantum image
classification in the context of remote sensing. After a brief outline of quantum computers …

In this paper, we present implementations of an annealing-based and a gate-based
quantum computing approach for finding the optimal policy to traverse a grid and compare …

Quantum computers have the potential to outshine classical alternatives in solving specific
problems, under the assumption of mature enough hardware. A specific subset of these …

Communication networks are managed more and more by using artificial intelligence.
Anomaly detection, network monitoring and user behaviour are areas where machine …