Implementation of quantum annealing: A systematic review

LP Yulianti, K Surendro - IEEE Access, 2022 - ieeexplore.ieee.org
Quantum annealing is a quantum computing approach widely used for optimization and
probabilistic sampling problems. It is an alternative approach designed due to the limitations …

[HTML][HTML] Quantum computing challenges in the software industry. A fuzzy AHP-based approach

U Awan, L Hannola, A Tandon, RK Goyal… - Information and Software …, 2022 - Elsevier
Context The current technology revolution has posed unexpected challenges for the
software industry. In recent years, the field of quantum computing (QC) technologies has …

On circuit-based hybrid quantum neural networks for remote sensing imagery classification

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 …

Practice and experience in using parallel and scalable machine learning in remote sensing from HPC over cloud to quantum computing

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 …

Detecting clouds in multispectral satellite images using quantum-kernel support vector machines

A Miroszewski, J Mielczarek, G Czelusta… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
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 …

Accurate image multi-class classification neural network model with quantum entanglement approach

F Riaz, S Abdulla, H Suzuki, S Ganguly, RC Deo… - Sensors, 2023 - mdpi.com
Quantum machine learning (QML) has attracted significant research attention over the last
decade. Multiple models have been developed to demonstrate the practical applications of …

Quantum-classical hybrid machine learning for image classification (iccad special session paper)

M Alam, S Kundu, RO Topaloglu… - 2021 IEEE/ACM …, 2021 - ieeexplore.ieee.org
Image classification is a major application domain for conventional deep learning (DL).
Quantum machine learning (QML) has the potential to revolutionize image classification. In …

A novel image classification framework based on variational quantum algorithms

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 …

[图书][B] Quantum-safe cryptography algorithms and approaches: Impacts of quantum computing on cybersecurity

SP Yadav, R Singh, V Yadav, F Al-Turjman, SA Kumar - 2023 - degruyter.com
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 …

Practice and experience in using parallel and scalable machine learning with heterogenous modular supercomputing architectures

M Riedel, R Sedona, C Barakat… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
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 …