Past, present, and future of face recognition: A review
Face recognition is one of the most active research fields of computer vision and pattern
recognition, with many practical and commercial applications including identification, access …
recognition, with many practical and commercial applications including identification, access …
Multi-factor authentication: A survey
Today, digitalization decisively penetrates all the sides of the modern society. One of the key
enablers to maintain this process secure is authentication. It covers many different areas of a …
enablers to maintain this process secure is authentication. It covers many different areas of a …
Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment
Biomimicry, adapting and implementing nature's designs provides an adequate first-order
solution to achieving superior mechanical properties. However, the design space is too vast …
solution to achieving superior mechanical properties. However, the design space is too vast …
De novo composite design based on machine learning algorithm
Composites are widely used to create tunable materials to achieve superior mechanical
properties. Brittle materials fail catastrophically in the presence of cracks. Incorporating …
properties. Brittle materials fail catastrophically in the presence of cracks. Incorporating …
Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry
Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that
can map the spatial distribution of molecules with high chemical specificity. IMS does not …
can map the spatial distribution of molecules with high chemical specificity. IMS does not …
Pseudo RGB-D face recognition
In the last decade, advances and popularity of low-cost RGB-D sensors have enabled us to
acquire depth information of objects. Consequently, researchers began to solve face …
acquire depth information of objects. Consequently, researchers began to solve face …
EEG signal classification using universum support vector machine
Support vector machine (SVM) has been used widely for classification of
electroencephalogram (EEG) signals for the diagnosis of neurological disorders such as …
electroencephalogram (EEG) signals for the diagnosis of neurological disorders such as …
A review and analysis of automatic optical inspection and quality monitoring methods in electronics industry
Electronics industry is one of the fastest evolving, innovative, and most competitive
industries. In order to meet the high consumption demands on electronics components …
industries. In order to meet the high consumption demands on electronics components …
Local binary patterns and its application to facial image analysis: a survey
Local binary pattern (LBP) is a nonparametric descriptor, which efficiently summarizes the
local structures of images. In recent years, it has aroused increasing interest in many areas …
local structures of images. In recent years, it has aroused increasing interest in many areas …
Multi-objective based spatio-temporal feature representation learning robust to expression intensity variations for facial expression recognition
Facial expression recognition (FER) is increasingly gaining importance in various emerging
affective computing applications. In practice, achieving accurate FER is challenging due to …
affective computing applications. In practice, achieving accurate FER is challenging due to …