Machine learning in the quantum realm: The state-of-the-art, challenges, and future vision
Abstract Machine learning has become a ubiquitous and effective technique for data
processing and classification. Furthermore, due to the superiority and progress of quantum …
processing and classification. Furthermore, due to the superiority and progress of quantum …
[HTML][HTML] Quantum machine learning: A review and case studies
A Zeguendry, Z Jarir, M Quafafou - Entropy, 2023 - mdpi.com
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 …
process. Practical computational efforts for training state-of-the-art models can now only be …
Improving the accuracy for analyzing heart diseases prediction based on the ensemble method
XY Gao, A Amin Ali, H Shaban Hassan… - Complexity, 2021 - Wiley Online Library
Heart disease is the deadliest disease and one of leading causes of death worldwide.
Machine learning is playing an essential role in the medical side. In this paper, ensemble …
Machine learning is playing an essential role in the medical side. In this paper, ensemble …
Scene semantic recognition based on modified fuzzy C-mean and maximum entropy using object-to-object relations
With advances in machine vision systems (eg, artificial eye, unmanned aerial vehicles,
surveillance monitoring) scene semantic recognition (SSR) technology has attracted much …
surveillance monitoring) scene semantic recognition (SSR) technology has attracted much …
Quantum machine learning in medical image analysis: A survey
L Wei, H Liu, J Xu, L Shi, Z Shan, B Zhao, Y Gao - Neurocomputing, 2023 - Elsevier
With the outstanding superposition and entanglement properties of quantum computing,
quantum machine learning has attracted widespread attention in many fields, such as …
quantum machine learning has attracted widespread attention in many fields, such as …
Performance One-step secant Training Method for Forecasting Cases
The training function used in the ANN method, especially backpropagation, can produce
different forecasting accuracy, depending on the method parameters given and the data to …
different forecasting accuracy, depending on the method parameters given and the data to …
Quantum machine learning applications in the biomedical domain: A systematic review
Quantum technologies have become powerful tools for a wide range of application
disciplines, which tend to range from chemistry to agriculture, natural language processing …
disciplines, which tend to range from chemistry to agriculture, natural language processing …
Quantum machine learning revolution in healthcare: a systematic review of emerging perspectives and applications
U Ullah, B Garcia-Zapirain - IEEE Access, 2024 - ieeexplore.ieee.org
Quantum computing (QC) stands apart from traditional computing systems by employing
revolutionary techniques for processing information. It leverages the power of quantum bits …
revolutionary techniques for processing information. It leverages the power of quantum bits …
Classification with quantum machine learning: A survey
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 …
applications such as cryptography, chemistry, Big data, machine learning, optimization …
A hybrid classical-quantum approach for multi-class classification
Quantum machine learning recently gained prominence due to the computational ability of
quantum computers in solving machine learning problems that are intractable on a classical …
quantum computers in solving machine learning problems that are intractable on a classical …