Human recognition with biometrics is a rapidly emerging area of computer vision. Compared
to other well-known biometric features such as the face, fingerprint, iris, and palmprint, the …

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 …

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 …

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 …

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

Ear images are easy to capture, and ear features are relatively stable and can be used for
identification. The ear images are all asymmetric, and the asymmetry of the ear images …

Biometric technology is fast gaining pace as a veritable developmental tool. So far, biometric
procedures have been predominantly used to ensure identity and ear recognition …

As an emerging biometric technology, human ear recognition has important applications in
crime tracking, forensic identification and other fields. In the paper, we propose an effective …

Reliable estimation of the atmospheric boundary layer height (ABLH) is critical for a range of
meteorological applications, including air quality assessment and weather forecasting …