The radial basis function (RBF) network has its foundation in the conventional approximation
theory. It has the capability of universal approximation. The RBF network is a popular …

Abstract The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the
second Competition-following the first very successful ABAW Competition held in …

This paper presents the baseline approach for the organized 2nd Covid-19 Competition,
occurring in the framework of the AIMIA Workshop in the European Conference on …

Early and reliable COVID-19 diagnosis based on chest 3-D CT scans can assist medical
specialists in vital circumstances. Deep learning methodologies constitute a main approach …

Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

The presence of Missing Values in a data set can affect the performance of a classifier
constructed using that data set as a training sample. Several methods have been proposed …

This paper presents an adaptive neural network, designed to improve the performance of
conventional automatic landing systems (ALS). Real-time learning was applied to train the …

In this study, we develop a design methodology for generalized radial basis function neural
networks. In contrast with the plethora of existing approaches, here we promote a …

In the ever-evolving field of digital communication systems, complex-valued neural networks
(CVNNs) have become a cornerstone, delivering exceptional performance in tasks like …

Deep neural networks (DNNs) are a powerful tool for solving complex problems. The
effectiveness of DNNs largely depends on the initialization technique used. This research …