Biometric recognition refers to the automated recognition of individuals based on their
biological and behavioral characteristics such as fingerprint, face, iris, and voice. The first …

Facial aging adversely impacts performance of face recognition and face verification and
authentication using facial features. This stochastic personalized inevitable process poses …

Understanding shadows from a single image consists of two types of task in previous
studies, containing shadow detection and shadow removal. In this paper, we present a multi …

To address the non-stationary property of aging patterns, age estimation can be cast as an
ordinal regression problem. However, the processes of extracting features and learning a …

In many real-world prediction tasks, class labels include information about the relative
ordering between labels, which is not captured by commonly-used loss functions such as …

Recent research has explored the possibility of extracting ancillary information from primary
biometric traits viz., face, fingerprints, hand geometry, and iris. This ancillary information …

Three-dimensional convolutional neural networks (3D CNN) of artificial intelligence (AI) are
potent in image processing and recognition using deep learning to perform generative and …

This paper presents a novel CNN model called Soft Stagewise Regression Network (SSR-
Net) for age estimation from a single image with a compact model size. Inspired by DEX, we …

Age estimation from facial images is typically cast as a nonlinear regression problem. The
main challenge of this problem is the facial feature space wrt ages is inhomogeneous, due …

In this paper, we propose an ordinal hyperplane ranking algorithm called OHRank, which
estimates human ages via facial images. The design of the algorithm is based on the relative …