This article highlights specific features of biological neurons and their dendritic trees, whose
adoption may help advance artificial neural networks used in various machine learning …

Brain-inspired computing (BIC) is an emerging research field that aims to build fundamental
theories, models, hardware architectures, and application systems toward more general …

Neural networks have proven to be a highly effective tool for solving complex problems in
many areas of life. Recently, their importance and practical usability have further been …

Following the successful application of vision transformers in multiple computer vision tasks,
these models have drawn the attention of the signal processing community. This is because …

We study a series of recognition tasks in two realistic scenarios requiring the analysis of
faces under strong occlusion. On the one hand, we aim to recognize facial expressions of …

Combining multiple machine learning models into an ensemble is known to provide superior
performance levels compared to the individual components forming the ensemble. This is …

Taking advantage of the latest advances in deep learning for seismology, we address
earthquake characterization from a data-driven perspective. Many of the usual procedures …

Speech emotion recognition (SER) is a field that has drawn a lot of attention due to its
applications in diverse fields. A current trend in methods used for SER is to leverage …

In this article, we present a novel approach for emotional speech lip-reading (EMOLIPS).
This two-level approach to emotional speech to text recognition based on visual data …

In agriculture, the timely identification of plant diseases is vital for reducing crop loss,
ensuring high-quality yields, and fostering sustainable farming practices. The agricultural …