Biometric technology is fast gaining pace as a veritable developmental tool. So far, biometric
procedures have been predominantly used to ensure identity and ear recognition …

This paper explores ear biometrics using a mixture of feature extraction techniques and
classifies this feature vector using deep learning with convolutional neural network. This …

This article presents an Industry 4.0 compliant ear biometric recognition technique using
dense convolutional network (DenseNet), a well-known convolutional neural network model …

This paper presents a technique for ear detection from 2D profile face images that is capable
of significantly reducing the false positives. In an ear biometrics system, recognition …

Feature extraction is important step to extract the useful and valuable information from the
electromyography (EMG) signal. However, the process of feature extraction requires prior …

Many image quality assessment algorithms (IQAs) have been developed during the past
decade. However, most of them are designed for images distorted by compression, noise …

The ear has emerged as a new biometric trait to recognize humans from their profile faces.
Stability over the years, noninvasive capturing process, expressionless images, and …

Biometrics is the recognition of a human using biometric characteristics for identification,
which may be physiological or behavioral. The physiological biometric features are the face …

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric
for the identification and recognition of humans due to its consistent shape and rich texture …

Automatic person recognition using ear shape images is an active field of research within
the biometric community. Similar to other biometric traits such as fingerprints, face and iris …