Efficient and reliable storage, analysis, and transmission of medical images are imperative
for accurate diagnosis, treatment, and management of various diseases. Since quantum …

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

Abstract Deep Convolutional Neural Network (CNN)-based image classification systems are
often susceptible to noise interruption, ie, minor image noise may significantly impact the …

Wind is an essential, clean and sustainable renewable source of energy; however, wind
speed is stochastic and intermittent. Accurate wind power generation forecasts are required …

One of the top causes of mortality in people globally is a brain tumor. Today, biopsy is
regarded as the cornerstone of cancer diagnosis. However, it faces difficulties, including low …

Abstract Despite advances in Deep Learning, the Convolutional Neural Networks methods
still manifest limitations in medical applications because datasets are usually restricted in …

Defect detection is crucial in the quality control of industrial applications. Existing supervised
methods are heavily reliant on the large amounts of labeled data. However, labeled data in …

This study introduces a quantum-inspired computational paradigm to address the
unresolved problem of Convolutional Neural Networks (CNNs) using the Rectified Linear …

Quantum-inspired Machine Learning (QiML) is a burgeoning field, receiving global attention
from researchers for its potential to leverage principles of quantum mechanics within …

Abstract Technologies such as Artificial Intelligence, Machine Learning, and Internet of
Things has made unobtrusive mental health monitoring a reality. Since, obtaining a large …