Automatic identity recognition from ear images is an active research topic in the biometric
community. The ability to secretly acquire images of the ear remotely and the stability of the …

Cooperative machine learning has many applications, such as data annotation, where an
initial model trained with partially labeled data is used to predict labels for unseen data …

In the era of big data, all types of data with increasing samples and high-dimensional
attributes are demonstrating their important roles in various fields, such as data mining …

Identity recognition using local features extracted from ear images has recently attracted a
great deal of attention in the intelligent biometric systems community. The rich and reliable …

This paper presents a comprehensive review of Automatic Facial Recognition Systems
using integrative and systematic mapping approach. The review is grounded on criteria …

Ear recognition is an active research area in the biometrics community with the ultimate goal
to recognize individuals effectively from ear images. Traditional ear recognition methods …

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 …

Recently, several deep learning schemes have been considered for recognizing ear print.
However, deep-based schemes are known to be data-hungry and they may require a …

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 …

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