Machine learning models have shown increased accuracy in classification ...
Energy-based models (EBM) have become increasingly popular within comput...
The performance of convolutional neural networks has continued to improv...
Remote photoplethysmography (rPPG) allows for noncontact monitoring of b...
Subtle periodic signals such as blood volume pulse and respiration can b...
Camera-based physiological monitoring, especially remote photoplethysmog...
Deep learning-based models generalize better to unknown data samples aft...
Research in presentation attack detection (PAD) for iris recognition has...
Face image synthesis has progressed beyond the point at which humans can...
Forensic iris recognition, as opposed to live iris recognition, is an
em...
Nonlinear iris texture deformations due to pupil size variations are one...
Iris recognition of living individuals is a mature biometric modality th...
Can deep learning models achieve greater generalization if their trainin...
Remote photoplethysmography (rPPG) is a technique for estimating blood v...
We present the Deception Detection and Physiological Monitoring (DDPM)
d...
Deep learning has driven remarkable accuracy increases in many computer
...
Remote photoplethysmography (rPPG) is a known family of techniques for
m...
Launched in 2013, LivDet-Iris is an international competition series ope...
This paper proposes the first known to us open source hardware and softw...
As the popularity of iris recognition systems increases, the importance ...
Diversity and unpredictability of artifacts potentially presented to an ...
Modern deep learning techniques can be employed to generate effective fe...
Gabor kernels are widely accepted as dominant filters for iris recogniti...
This paper proposes an end-to-end iris recognition method designed
speci...
With increasing interest in employing iris biometrics as a forensic tool...
This paper proposes the first known to us iris recognition methodology
d...
Convolutional neural networks (CNNs) for biomedical image analysis are o...
Subject matching performance in iris biometrics is contingent upon fast,...
This paper offers three new, open-source, deep learning-based iris
segme...
The adoption of large-scale iris recognition systems around the world ha...
We propose a new iris presentation attack detection method using
three-d...
This paper proposes the first, known to us, open source presentation att...
This chapter provides insight on how iris recognition, one of the leadin...
This paper presents a database of iris images collected from disease aff...
This paper presents the experimental study revealing weaker performance ...
This paper presents a unique analysis of post-mortem human iris recognit...
This paper presents an analysis of how the iris recognition is impacted ...
This paper presents the most comprehensive analysis of iris recognition
...
This paper presents a unique study of post-mortem human iris recognition...
This paper presents an analysis of how iris recognition is influenced by...
Binarized statistical image features (BSIF) have been successfully used ...
This paper advances the state of the art in human examination of iris im...
This paper presents a method for segmenting iris images obtained from th...
This paper presents a deep-learning-based method for iris presentation a...
With post-mortem iris recognition getting increasing attention throughou...
This paper presents a comprehensive study of post-mortem human iris
reco...
Iris recognition is increasingly used in large-scale applications. As a
...