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 …

Biometrics is becoming an important technology in automated person recognition. With the
help of biometrics, the individuals are recognized through their unique characteristics and …

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 …

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 …

The recognition performance of visual recognition systems is highly dependent on extracting
and representing the discriminative characteristics of image data. Convolutional neural …

This paper employs state-of-the-art Deep Convolutional Neural Networks (CNNs), namely
AlexNet, VGGNet, Inception, ResNet and ResNeXt in a first experimental study of ear …

This paper presents ear recognition models constructed with Deep Residual Networks
(ResNet) of various depths. Due to relatively limited amounts of ear images we propose …

In this paper, we propose an unsupervised lightweight network with a single layer for ear
print recognition. We refer to this method by MDFNet because it relies on gradient …

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 …

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 …