Context The current technology revolution has posed unexpected challenges for the software industry. In recent years, the field of quantum computing (QC) technologies has …
A Sebastianelli, DA Zaidenberg… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
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 …
M Riedel, G Cavallaro… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Using computationally efficient techniques for transforming the massive amount of Remote Sensing (RS) data into scientific understanding is critical for Earth science. The utilization of …
Support vector machines (SVMs) are well-established classifiers that are effectively deployed in an array of classification tasks. In this article, we consider extending classical …
Quantum machine learning (QML) has attracted significant research attention over the last decade. Multiple models have been developed to demonstrate the practical applications of …
Image classification is a major application domain for conventional deep learning (DL). Quantum machine learning (QML) has the potential to revolutionize image classification. In …
Y Chen - Quantum Information Processing, 2024 - Springer
Image classification is a crucial task in machine learning with widespread practical applications. The existing classical framework for image classification typically utilizes a …
Quantum computers have demonstrated that they have the inherent potential to outperform classical computers in many areas. One of the major impacts is that the currently available …
We observe a continuously increased use of Deep Learning (DL) as a specific type of Machine Learning (ML) for data-intensive problems (ie,'big data') that requires powerful …