Abstract Machine learning has become a ubiquitous and effective technique for data
processing and classification. Furthermore, due to the superiority and progress of quantum …

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 …

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 …

With advances in machine vision systems (eg, artificial eye, unmanned aerial vehicles,
surveillance monitoring) scene semantic recognition (SSR) technology has attracted much …

With the outstanding superposition and entanglement properties of quantum computing,
quantum machine learning has attracted widespread attention in many fields, such as …

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 …

Quantum technologies have become powerful tools for a wide range of application
disciplines, which tend to range from chemistry to agriculture, natural language processing …

Quantum computing (QC) stands apart from traditional computing systems by employing
revolutionary techniques for processing information. It leverages the power of quantum bits …

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 …

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 …