Deep learning has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

Wind power generation is always associated with uncertainties as a result of fluctuations of
wind speed. Accurate predictions of wind power generation are important for the efficient …

Twitter sentiment detectors (TSDs) provide a better solution to evaluate the quality of service
and product than other traditional technologies. The classification accuracy and detection …

Environmental monitoring has become an active research area due to the current rise in the
global climate change crises. Current environmental monitoring solutions, however, are …

Short-term electric load forecasting is essential for the operation of power systems and the
power market, including economic dispatch, unit commitment, peak load shaving, load …

Since the rise of deep learning in the past few years, convolutional neural networks (CNNs)
have quickly found their place within the remote sensing (RS) community. As a result, they …

This paper presents a framework for integrating Explainable and Anomalous Machine
Learning (EAML) into a digital twin to enable finetuning of mixtures as a mean to realize next …

Fraudulent transactions and how to detect them remain a significant problem for financial
institutions around the world. The need for advanced fraud detection systems to safeguard …

Batch Size is an essential hyper-parameter in deep learning. Different chosen batch sizes
may lead to various testing and training accuracies and different runtimes. Choosing an …