The problem of distinguishing identical twins and non-twin look-alikes i...
We present a quality-aware multimodal recognition framework that combine...
In this paper, we consider the challenge of face morphing attacks, which...
Morphing is the process of combining two or more subjects in an image in...
In recent years, cross-spectral iris recognition has emerged as a promis...
In recent years, with the advent of deep-learning, face recognition has
...
Morphed images have exploited loopholes in the face recognition checkpoi...
Face recognition systems are extremely vulnerable to morphing attacks, i...
While working with fingerprint images acquired from crime scenes, mobile...
This work investigates the well-known problem of morphing attacks, which...
Performance of fingerprint recognition algorithms substantially rely on ...
Semi-Supervised Learning (SSL) approaches have been an influential frame...
In this paper, we present a novel differential morph detection framework...
Although biometric facial recognition systems are fast becoming part of
...
In this paper, we propose a framework for disentangling the appearance a...
Deep neural networks are susceptible to adversarial manipulations in the...
Deep neural networks have presented impressive performance in biometric
...
Adversarial examples have recently proven to be able to fool deep learni...
The state-of-the-art performance of deep learning algorithms has led to ...
In this paper a novel cross-device text-independent speaker verification...
Performing recognition tasks using latent fingerprint samples is often
c...
In this paper, we propose a deep multimodal fusion network to fuse multi...
In this paper, we propose to employ a bank of modality-dedicated
Convolu...
In this paper, we propose a new deep framework which predicts facial
att...
Audio-visual recognition (AVR) has been considered as a solution for spe...
In this paper, a novel method using 3D Convolutional Neural Network (3D-...