Sparse (fast) representations of deterministic signals have been well studied. Among other
types, there exists one called adaptive Fourier decomposition (AFD) for functions in analytic …

Deep learning-based hyperspectral image (HSI) classification methods have recently shown
excellent performance, however, there are two shortcomings that need to be addressed …

The Electrocardiogram (ECG) signal is increasing in popularity as a biometric modality due
to its useful properties in developing trustworthy identification systems. However, one of the …

Music genre classification (MGC) has gained significant attention due to its broad
applications in music information retrieval. Traditional MGC approaches often rely on hand …

This article investigates the potential of surface electromyography (sEMG) as a new
biometric modality and proposes a deep neural network architecture as the backbone of a …

Recently, hyperspectral image (HSI) classification methods based on deep learning (DL)
have demonstrated excellent performance. However, these DL methods still face two major …

Electrocardiography (ECG) has been a subject of research interest in human identification
because it is a promising biometric trait that is believed to have discriminatory …

Abstract Integration of Artificial Intelligence (AI) into areas such as image classification,
speech recognition, natural language processing, and autonomous systems illustrates its …

This study examines the efficacy of an ECG-based biometric recognition model,
concentrating specifically on the influence of iteration configurations and the quantity of …