Results 81 to 90 of about 2,977,466 (210)

Implementation and Performance Evaluation of Quantum Machine Learning Algorithms for Binary Classification

Software
In this work, we studied the use of Quantum Machine Learning (QML) algorithms for binary classification and compared their performance with classical Machine Learning (ML) methods. QML merges principles of Quantum Computing (QC) and ML, offering improved
Surajudeen Shina Ajibosin, Deniz Cetinkaya   +1 more
doaj   +1 more source

Quantum computing with exciton-polariton condensates

, 2020
10.1038/s41534-020-0244-xnpj Quantum ...
Liew, T.C.H., Ghosh, Sanjib, Ghosh, S., Liew, Timothy C. H.   +3 more
core   +1 more source

Quantum reservoir processing

, 2019
The concurrent rise of artificial intelligence and quantum information poses an opportunity for creating interdisciplinary technologies like quantum neural networks.
Opala, A., Liew, T.C.H., Ghosh, Sanjib, Ghosh, S., Opala, Andrzej, Matuszewski, M., Paterek, T., Liew, Timothy C. H., Paterek, Tomasz, Matuszewski, Michał   +9 more
core   +1 more source

Classification using a two-qubit quantum chip [PDF]

, 2020
Quantum computing has great potential for advancing machine learning algorithms beyond classical reach. Even though full-fledged universal quantum computers do not exist yet, its expected benefits for machine learning can already be shown using ...
Neumann, Niels M. P., Niels M. P. Neumann   +1 more
core   +1 more source

A hybrid quantum-classical classification model based on branching multi-scale entanglement renormalization ansatz

Scientific Reports
Tensor networks are emerging architectures for implementing quantum classification models. The branching multi-scale entanglement renormalization ansatz (BMERA) is a tensor network known for its enhanced entanglement properties.
Yan-Yan Hou, Jian Li, Tao Xu, Xin-Yu Liu
doaj   +1 more source

Classification with Quantum Machine Learning: A Survey

CoRR, 2020
Due to the superiority and noteworthy progress of Quantum Computing (QC) in a lot of applications such as cryptography, chemistry, Big data, machine learning, optimization, Internet of Things (IoT), Blockchain, communication, and many more. Fully towards to combine classical machine learning (ML) with Quantum Information Processing (QIP) to build a new
Zainab Abohashima, Mohamed Elhoseny, Essam H. Houssein, Waleed M. Mohamed   +3 more
openaire   +3 more sources

Quantum image classification using principal component analysis [PDF]

, 2015
We present a novel quantum algorithm for the classification of images. The algorithm is constructed using principal component analysis and von Neuman quantum measurements.
Ostaszewski, M., Sadowski, P., Gawron, P.   +2 more
core   +1 more source

Book of Abstracts for the European Quantum Technologies Conference (EQTC) 2023

The EQTC 2023 held from October 16th to October 20th, 2023, in Hannover, was a week of conference and exhibition. The conference featured over 40 exhibitors, more than two-dozen plenary presentations and panel discussions, over 140 speakers and 180 ...
Quantum Valley Lower Saxony
core   +1 more source

Quantum Computing Meets Deep Learning: A QCNN Model for Accurate and Efficient Image Classification

Mathematics
In deep learning, Convolutional Neural Networks (CNNs) serve as fundamental models, leveraging the correlational structure of data for tasks such as image classification and processing.
Sunil Prajapat, Manish Tomar, Pankaj Kumar, Rajesh Kumar, Athanasios V. Vasilakos   +4 more
doaj   +1 more source

Optimizing Quantum Classification Algorithms on Classical Benchmark Datasets. [PDF]

Entropy (Basel), 2023
John M, Schuhmacher J, Barkoutsos P, Tavernelli I, Tacchino F.   +4 more
europepmc   +1 more source