Recurrent neural networks (RNNs) have significantly advanced the field of machine learning
(ML) by enabling the effective processing of sequential data. This paper provides a …

Although epilepsy is one of the most prevalent and ancient neurological disorder, but, still
difficult to identify the specific type of seizure, due to artefacts, noise, and other disturbances …

Machine learning (ML) plays a crucial role in power systems by providing advanced tools for
data analysis, pattern recognition, and decision making. Some of the key applications of …

Detection of the Eye State can be helpful in several ways since it can be used as an
indication of mental disorders, energetics in aging, detection of alcoholism, and detection of …

Lung diseases are the most common ailments seen among people with the history of
smoking. Prompt and timely recognition and diagnosis may help in saving many lives. In …

In this paper, an effort would be made to provide a review of current state of the development
of artificial glands within endocrine neural networks. The main goal is to systematize the …

Background: Epileptic Seizure type diagnosis is done by clinician based on the symptoms
during the episode and the Electroencephalograph (EEG) recording taken during inter-ictal …

The lunar calendar is often overlooked in time series data modelling, despite its importance
in understanding seasonal patterns as well as economic, natural phenomena, and …

People with reduced vision or total blindness frequently have trouble navigating new
environments on their own. It can be difficult to travel or even just stroll down a busy street …

Анотація Магістерська дисертація: 111 с., 29 табл., 22 рис., 40 посилань, 1 додаток.
Актуальність даної роботи полягає в необхідності створення надійних систем …