Automatic identity recognition from ear images represents an active field of research within
the biometric community. The ability to capture ear images from a distance and in a covert …

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 …

Ear recognition technology has long been dominated by (local) descriptor-based techniques
due to their formidable recognition performance and robustness to various sources of image …

Identity recognition from ear images is an active field of research within the biometric
community. The ability to capture ear images from a distance and in a covert manner makes …

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 …

Recognizing people by their ear has recently received significant attention in the literature.
Several reasons account for this trend: first, ear recognition does not suffer from some …

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 …

Human recognition systems based on biometrics are much in demand due to increasing
concerns of security and privacy. The human ear is unique and useful for recognition. It …

The possibility of identifying people by the shape of their outer ear was first discovered by
the French criminologist Bertillon, and refined by the American police officer Iannarelli, who …

The authors present an unconstrained ear recognition framework that outperforms state‐of‐
the‐art systems in different publicly available image databases. To this end, they developed …