Time-frequency (TF) based machine learning methodologies can improve the design of
classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF …

Often, emotional disorders are overlooked due to their lack of awareness, resulting in
potential mental issues. Recent advances in sensing and inference technology provide a …

Carotid-to-femoral pulse wave velocity (cf-PWV) is considered a critical index to evaluate
arterial stiffness. For this reason, estimating Carotid-to-femoral pulse wave velocity (cf-PWV) …

Sažetak With the recent developments of technology and the advances in artificial intelligent
and machine learning techniques, it becomes possible for the robot to acquire and show the …

This study demonstrates that a time-frequency (TF) image pattern recognition approach
offers significant advantages over standard signal classification methods that use t-domain …

Current developments in deep neural architectures achieved remarkable results in the
classification of emotions from speech. Recently, also cross-modal approaches gained …

Accumulating studies appear to suggest that the risk factors for venous thromboembolism
(VTE) among young-middle-aged inpatients are different from those among elderly people …

This paper's core objective is to develop and validate a new neurocomputing model to
classify document images in particularly demanding hard conditions such as image …

Automated visual inspection (AVI) attracts increasing interest in product quality control both
academic and industrial communities, particularly on mass production processes, because …

In this paper, we propose a new methodology for emotional speech recognition using visual
deep neural network models. We employ the transfer learning capabilities of the pre-trained …