Deep learning for iris recognition: A survey
In this survey, we provide a comprehensive review of more than 200 articles, technical
reports, and GitHub repositories published over the last 10 years on the recent …
reports, and GitHub repositories published over the last 10 years on the recent …
CYBORG: Blending human saliency into the loss improves deep learning-based synthetic face detection
Can deep learning models achieve greater generalization if their training is guided by
reference to human perceptual abilities? And how can we implement this in a practical …
reference to human perceptual abilities? And how can we implement this in a practical …
The value of ai guidance in human examination of synthetically-generated faces
Face image synthesis has progressed beyond the point at which humans can effectively
distinguish authentic faces from synthetically-generated ones. Recently developed synthetic …
distinguish authentic faces from synthetically-generated ones. Recently developed synthetic …
Human-aided saliency maps improve generalization of deep learning
Deep learning has driven remarkable accuracy increases in many computer vision
problems. One ongoing challenge is how to achieve the greatest accuracy in cases where …
problems. One ongoing challenge is how to achieve the greatest accuracy in cases where …
Human saliency-driven patch-based matching for interpretable post-mortem iris recognition
Forensic iris recognition, as opposed to live iris recognition, is an emerging research area
that leverages the discriminative power of iris biometrics to aid human examiners in their …
that leverages the discriminative power of iris biometrics to aid human examiners in their …
Cyborg: Blending human saliency into the loss improves deep learning
Can deep learning models achieve greater generalization if their training is guided by
reference to human perceptual abilities? And how can we implement this in a practical …
reference to human perceptual abilities? And how can we implement this in a practical …
Misclassifications of contact lens iris PAD algorithms: Is it gender bias or environmental conditions?
One of the critical steps in biometrics pipeline is detection of presentation attacks, a physical
adversary. Several presentation (adversary) attack detection (PAD) algorithms, including iris …
adversary. Several presentation (adversary) attack detection (PAD) algorithms, including iris …
Model focus improves performance of deep learning-based synthetic face detectors
Deep learning-based models generalize better to unknown data samples after being guided
“where to look” by incorporating human perception into training strategies. We made an …
“where to look” by incorporating human perception into training strategies. We made an …
Deformirisnet: An identity-preserving model of iris texture deformation
Nonlinear iris texture deformations due to pupil size variations are one of the main factors
responsible for within-class variance of genuine comparison scores in iris recognition. In …
responsible for within-class variance of genuine comparison scores in iris recognition. In …
Training Better Deep Learning Models Using Human Saliency
This work explores how human judgement about salient regions of an image can be
introduced into deep convolutional neural network (DCNN) training. Traditionally, training of …
introduced into deep convolutional neural network (DCNN) training. Traditionally, training of …