Traditional handcrafted crowd-counting techniques in an image are currently transformed
via machine-learning and artificial-intelligence techniques into intelligent crowd-counting …

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 …

In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …

The research presented in this paper focuses on Head-Related Transfer Function (HRTF)
individualization using deep learning techniques. HRTF individualization is paramount for …

In the computer vision applications such as security surveillance and robotics, pedestrian
identification shows much attention in the last decade. This is usually achieved by human …

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 …

Ear biometrics is an appealing choice for human recognition in various daily activities,
ranging from surveillance to commercial-related applications. It has multiple advantages in …

Ear recognition is a new kind of biometric identifification technology now. Feature extraction
is a key step in pattern recognition technology, which determines the accuracy of …

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 …

This chapter introduces COM-Ear, a deep constellation model for ear recognition. Different
from competing solutions, COM-Ear encodes global as well as local characteristics of ear …