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20152024
most cited3D Convolutional Neural Networks for Cross Audio-Visual Matching Recognition

119 citations · 388 across the 56 of their papers we have counts for

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Showing 2020 · cs.CVShow all

14 papers · 2 filters

cs.CV2020★ 87 cited

Deep Hashing for Secure Multimodal Biometrics

Veeru Talreja, Matthew Valenti, Nasser Nasrabadi

When compared to unimodal systems, multimodal biometric systems have several advantages, including lower error rate, higher accuracy, and larger population coverage. However, multi…

cs.CV2020

Super-resolution Guided Pore Detection for Fingerprint Recognition

Syeda Nyma Ferdous, Ali Dabouei, Jeremy Dawson +1

Performance of fingerprint recognition algorithms substantially rely on fine features extracted from fingerprints. Apart from minutiae and ridge patterns, pore features have proven…

cs.CV2020

Differential Morphed Face Detection Using Deep Siamese Networks

Sobhan Soleymani, Baaria Chaudhary, Ali Dabouei +2

Although biometric facial recognition systems are fast becoming part of security applications, these systems are still vulnerable to morphing attacks, in which a facial reference i…

cs.CV2020

Mutual Information Maximization on Disentangled Representations for Differential Morph Detection

Sobhan Soleymani, Ali Dabouei, Fariborz Taherkhani +2

In this paper, we present a novel differential morph detection framework, utilizing landmark and appearance disentanglement. In our framework, the face image is represented in the…

cs.CV2020

Matching Distributions via Optimal Transport for Semi-Supervised Learning

Fariborz Taherkhani, Hadi Kazemi, Ali Dabouei +2

Semi-Supervised Learning (SSL) approaches have been an influential framework for the usage of unlabeled data when there is not a sufficient amount of labeled data available over th…

cs.CV2020

Cross-Spectral Iris Matching Using Conditional Coupled GAN

Moktari Mostofa, Fariborz Taherkhani, Jeremy Dawson +1

Cross-spectral iris recognition is emerging as a promising biometric approach to authenticating the identity of individuals. However, matching iris images acquired at different spe…