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

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 …

In this paper we present the results of the Unconstrained Ear Recognition Challenge
(UERC), a group benchmarking effort centered around the problem of person recognition …

Extraction and description of image features is an active research topic and important for
several applications of computer vision field. This paper presents a new noise-tolerant and …

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 …

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 …

Object detection and segmentation represents the basis for many tasks in computer and
machine vision. In biometric recognition systems the detection of the region‐of‐interest (ROI) …

Ear recognition has seen multiple improvements in recent years and still remains very active
today. However, it has been approached from recognition and detection perspective …

The analysis of kin relations from visual data represents a challenging research problem
with important real-world applications. However, research in this area has mostly been …

Automatic ear recognition is gaining popularity within the research community due to
numerous desirable properties, such as high recognition performance, the possibility of …