The authors perform unconstrained ear recognition using transfer learning with deep neural
networks (DNNs). First, they show how existing DNNs can be used as a feature extractor …

Getting to an ear recognition model that can overcome all challenges and difficulties was
and still the main objective of researchers for years. One particular problem we highlight …

Ear based identity recognition subject to uncontrolled conditions such as illumination
changes, pose variation, low contrast, partial occlusion and noise, is an active research area …

Identification systems based on biometric features are becoming increasingly important. One
of the most common biometric features is the ear. The accuracy of these systems is heavily …

As one of the most important biometrics, ear biometrics is getting more and more attention.
Ear recognition has unique advantages and can make identification more secure and …

Automatic identity recognition of ear images represents an active area of interest within the
biometric community. The human ear is a perfect source of data for passive person …

Recently, deep convolutional neural networks (CNNs) have been used for ear recognition
with the increasing and available ear image databases. However, most known ear …

Person identifications using the ear-based biometric system has become quite popular in
recent year due to increasing demands in security and surveillance applications. With …

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

Principal Component Analysis (PCA) has been successfully applied to many applications,
including ear recognition. This paper presents a 2D Wavelet based Multi-Band Principal …