Quantum convolutional neural network based on variational quantum circuits
Abstract Machine learning algorithms are becoming increasingly resource-intensive. In
contrast to classical computing, quantum computing holds the potential with exponential …
contrast to classical computing, quantum computing holds the potential with exponential …
Programming quantum neural networks on NISQ systems: an overview of technologies and methodologies
S Markidis - Entropy, 2023 - mdpi.com
Noisy Intermediate-Scale Quantum (NISQ) systems and associated programming interfaces
make it possible to explore and investigate the design and development of quantum …
make it possible to explore and investigate the design and development of quantum …
QMFND: A quantum multimodal fusion-based fake news detection model for social media
Z Qu, Y Meng, G Muhammad, P Tiwari - Information Fusion, 2024 - Elsevier
Fake news is frequently disseminated through social media, which significantly impacts
public perception and individual decision-making. Accurate identification of fake news on …
public perception and individual decision-making. Accurate identification of fake news on …
Quantum machine learning for image classification
A Senokosov, A Sedykh, A Sagingalieva… - Machine Learning …, 2024 - iopscience.iop.org
Image classification, a pivotal task in multiple industries, faces computational challenges
due to the burgeoning volume of visual data. This research addresses these challenges by …
due to the burgeoning volume of visual data. This research addresses these challenges by …
Hybrid quantum-classical convolutional neural network model for image classification
Image classification plays an important role in remote sensing. Earth observation (EO) has
inevitably arrived in the big data era, but the high requirement on computation power has …
inevitably arrived in the big data era, but the high requirement on computation power has …
Advances in Quantum Machine Learning and Deep learning for image classification: a Survey
R Kharsa, A Bouridane, A Amira - Neurocomputing, 2023 - Elsevier
Image classification, which is a fundamental element of Computer Vision (CV) and Artificial
Intelligence (AI), has been researched intensively in numerous domains and embedded in …
Intelligence (AI), has been researched intensively in numerous domains and embedded in …
A hybrid quantum-classical neural network architecture for binary classification
D Arthur - arXiv preprint arXiv:2201.01820, 2022 - arxiv.org
Deep learning is one of the most successful and far-reaching strategies used in machine
learning today. However, the scale and utility of neural networks is still greatly limited by the …
learning today. However, the scale and utility of neural networks is still greatly limited by the …
A fully connected quantum convolutional neural network for classifying ischemic cardiopathy
U Ullah, AGO Jurado, ID Gonzalez… - IEEE …, 2022 - ieeexplore.ieee.org
The prevalence of heart diseases is rising quickly throughout the world, which has an impact
on both the world economy and public health. According to the recent statistical survey …
on both the world economy and public health. According to the recent statistical survey …
Quantum-classical convolutional neural networks in radiological image classification
Quantum machine learning is receiving significant attention currently, but its usefulness in
comparison to classical machine learning techniques for practical applications remains …
comparison to classical machine learning techniques for practical applications remains …
Novel transfer learning based deep features for diagnosis of down syndrome in children using facial images
Down syndrome is a chromosomal condition characterized by the existence of an additional
copy of chromosome 21. This genetic anomaly leads to a range of developmental …
copy of chromosome 21. This genetic anomaly leads to a range of developmental …