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Case-Based and Quantum Classification for ERP-Based Brain–Computer Interfaces [PDF]

Brain Sciences, 2023
Low transfer rates are a major bottleneck for brain–computer interfaces based on electroencephalography (EEG). This problem has led to the development of more robust and accurate classifiers.
Grégoire H. Cattan, Alexandre Quemy
doaj   +2 more sources

On Quantum Methods for Machine Learning Problems Part II: Quantum Classification Algorithms

Big Data Mining and Analytics, 2020
This is a review of quantum methods for machine learning problems that consists of two parts. The first part, "quantum tools", presented some of the fundamentals and introduced several quantum tools based on known quantum search algorithms.
Farid Ablayev, Marat Ablayev, Joshua Zhexue Huang, Kamil Khadiev, Nailya Salikhova, Dingming Wu   +5 more
doaj   +3 more sources

Rheumatoid arthritis classification using hybrid pretrained quantum convolutional neural network [PDF]

Frontiers in Artificial Intelligence
Rheumatoid arthritis (RA) is a chronic autoimmune disease where early diagnosis is critical for preventing irreversible joint damage. Recent advances in quantum computing have established potential advantages in modelling complex, high-dimensional ...
D. Jeyamani, Rukmani Panjanathan
doaj   +2 more sources

Multiclass classification using quantum convolutional neural networks with hybrid quantum-classical learning

Frontiers in Physics, 2022
Multiclass classification is of great interest for various applications, for example, it is a common task in computer vision, where one needs to categorize an image into three or more classes.
Denis Bokhan, Denis Bokhan, Alena S. Mastiukova, Alena S. Mastiukova, Aleksey S. Boev, Dmitrii N. Trubnikov, Aleksey K. Fedorov, Aleksey K. Fedorov   +7 more
doaj   +3 more sources

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   +2 more sources

Quantum Machine Learning: A Review and Case Studies

Entropy, 2023
Despite its undeniable success, classical machine learning remains a resource-intensive process. Practical computational efforts for training state-of-the-art models can now only be handled by high speed computer hardware.
Amine Zeguendry, Zahi Jarir, Mohamed Quafafou   +2 more
doaj   +1 more source

Indoor–Outdoor Detection in Mobile Networks Using Quantum Machine Learning Approaches

Computers, 2021
Communication networks are managed more and more by using artificial intelligence. Anomaly detection, network monitoring and user behaviour are areas where machine learning offers advantages over more traditional methods.
Frank Phillipson, Robert S. Wezeman, Irina Chiscop   +2 more
doaj   +1 more source

A Grover-search based quantum learning scheme for classification

New Journal of Physics, 2021
The hybrid quantum–classical learning scheme provides a prominent way to achieve quantum advantages on near-term quantum devices. A concrete example toward this goal is the quantum neural network (QNN), which has been developed to accomplish various ...
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao   +3 more
doaj   +1 more source

RETRACTED: Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree

Frontiers in Physics, 2023
This study highlights the drawbacks of current quantum classifiers that limit their efficiency and data processing capabilities in big data environments.
Naihua Ji, Rongyi Bao, Xiaoyi Mu, Zhao Chen, Xin Yang, Shumei Wang   +5 more
doaj   +1 more source

Support Vector Machines with Quantum State Discrimination

Quantum Reports, 2021
We analyze possible connections between quantum-inspired classifications and support vector machines. Quantum state discrimination and optimal quantum measurement are useful tools for classification problems.
Roberto Leporini, Davide Pastorello
doaj   +1 more source