In this paper, we propose a robust face recognition model called DeepWTPCA-L 1 using
WTPCA-L 1 features and a CNN-LSTM architecture. First, WTPCA-L 1 algorithm, composed …

Over the last two decades, face recognition (FR) has become one of the most prevailing
biometric applications for effective people identification as it offers practical advantages over …

Of late, biometric systems are ubiquitous to provide user authentication and security. With
the advent of AI aided computer vision, face recognition systems are the new age biometrics …

Low resolution (LR) and very low resolution (VLR) face images captured by surveillance
cameras make automatic face recognition (AFR) a challenging task. The performance of an …

In the last ten years, many variants of the principal component analysis were suggested to
fight against the curse of dimensionality. Recently, A. Sharma et al. have proposed a stable …

Face recognition (FR) is getting a lot of attention for a good reason in the field of research
and making a big impact in areas such as computer vision and human-computer interaction …

Several methods employing 2DPCA for dimensionality reduction have exhibited limitations
in classification accuracy. Angle Two-Dimensional Principal Component Analysis (Angle …

Multimodal data fusion is a powerful methodology for improving the accuracy of biometric
authentication systems that use modalities such as face, voice, and fingerprints. Essentially …

Since the last two decades, face recognition has been a significant area in the fields of
biometrics and machine learning that uses the different appearances and geometric-based …

Face recognition is considered the main physiological and behavioral biometrics due to the
following advantages; simplicity of the face capturing, feature uniqueness and distinctness …