EEG experts can assess a newborn's brain maturity by visual analysis of age-related
patterns in sleep EEG. It is highly desirable to make the results of assessment most accurate …

The deep architecture of today's behemoth “foundation” Artificial Neural Network (ANN)
models came to be not only because we can do that utilizing computational capabilities of …

In this paper, we attempt to verify a hypothesis of informational efficiency of financial
markets, known as “random walk” introduced by Fama. Such hypotheses could be …

We investigate a number of Artificial Neural Network architectures (well-known and more
“exotic”) in application to the long-term financial time-series forecasts of indexes on different …

We propose to use a hybrid Convolutional-Multilayer Perceptron Neural Network (CNN-
MLP) architecture to learn high gamma EEG features for person recognition. An original …

The catastrophic forgetting of the previously learned patterns during continuous life-long re-
training of the models is a well-known machine learning problem. We propose an explicit …

Object recognition is a large application area of Machine Learning (ML) aiming to design
solutions to autonomous driving capable to accurately identify traffic signs. Such …

Contemporary e-mail services have high availability expectations from the customers and
are resource-strained because of the high-volume throughput and spam attacks. Deep …

A theory of Efficient Market Hypothesis (EMH) has been introduced by Fama to analyse
financial markets. In particular the EMH theory has been proven in real cases under different …

We describe an experimental approach to design a Fraud Detection system using
supervised Machine Learning (ML) methods such as decision trees and random forest. We …