Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …

Due to the digitization and Internet of Things revolutions, the present electronic world has a
wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a …

Regression analysis makes up a large part of supervised machine learning, and consists of
the prediction of a continuous independent target from a set of other predictor variables. The …

The loss function, also known as cost function, is used for training a neural network or other
machine learning models. Over the past decade, researchers have designed many loss …

Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …

Abstract Time Series Forecasting has been an active area of research due to its many
applications ranging from network usage prediction, resource allocation, anomaly detection …

Modern single-particle-tracking techniques produce extensive time-series of diffusive motion
in a wide variety of systems, from single-molecule motion in living-cells to movement …

Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for
revolutionizing data analysis and applications in many domains of Earth sciences. This …

Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …

Artificial intelligence in health care has experienced remarkable innovation and progress in
the last decade. Significant advancements can be attributed to the utilization of artificial …