The implementation of face recognition techniques in an embedded system is a very
important aspect of various security applications, such as authorization identification in cash …

The extraction of required features from the facial image is an important primitive task for
face recognition. This paper evaluates different nonlinear feature extraction approaches …

This paper proposes face recognition based on dominant frequency feature and
multiresolution metrics. Dominant frequency feature is a small part of face frequency …

Images from embedded sensors need digital processing to recover high-quality images and
to extract features of a scene. Depending on the properties of the sensor and on the …

In this paper we propose features based on sub-space projection methods using Principal
Component Analysis (PCA) and Independent Component Analysis (ICA) on wavelet sub …

We describe an analog-VLSI neural network for face recognition based on subspace
methods. The system uses a dimensionality-reduction network whose coefficients can be …

Typical image recognition systems operate in two stages: feature extraction to reduce the
dimensionality of the input space, and classification based on the extracted features. Analog …

The human skill of identifying thousands of people even after so many years excited many
researchers to focus on face recognition systems. The majority of real world applications …

This paper presents the use of a deep learning convolutional neural network to recognize
different human faces images. This study used three pre-trained deep CNN models to solve …

Image-based face recognition is a challenging problem due to variations in pose,
expression and illumination. Techniques that can provide effective feature representation …