activity
20152022
most cited3D Convolutional Neural Networks for Cross Audio-Visual Matching Recognition

119 citations · 354 across the 34 of their papers we have counts for

collaborators

66 papers

q-bio.GN2021

Human Age Estimation from Gene Expression Data using Artificial Neural Networks

Salman Mohamadi, Gianfranco. Doretto, Nasser M. Nasrabadi +1

The study of signatures of aging in terms of genomic biomarkers can be uniquely helpful in understanding the mechanisms of aging and developing models to accurately predict the age…

cs.CV20211 cited

Adversarially Perturbed Wavelet-based Morphed Face Generation

Kelsey O'Haire, Sobhan Soleymani, Baaria Chaudhary +3

Morphing is the process of combining two or more subjects in an image in order to create a new identity which contains features of both individuals. Morphed images can fool Facial…

cs.CV2021

Attribute-Based Deep Periocular Recognition: Leveraging Soft Biometrics to Improve Periocular Recognition

Veeru Talreja, Nasser M. Nasrabadi, Matthew C. Valenti

In recent years, periocular recognition has been developed as a valuable biometric identification approach, especially in wild environments (for example, masked faces due to COVID-…

cs.CV20212 cited

Quality Map Fusion for Adversarial Learning

Uche Osahor, Nasser M. Nasrabadi

Generative adversarial models that capture salient low-level features which convey visual information in correlation with the human visual system (HVS) still suffer from perceptibl…

cs.CV2021

Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning

Uche Osahor, Nasser M. Nasrabadi

In few-shot classification, the primary goal is to learn representations from a few samples that generalize well for novel classes. In this paper, we propose an efficient low displ…

cs.AI2021

Deep adversarial attack on target detection systems

Uche M. Osahor, Nasser M. Nasrabadi

Target detection systems identify targets by localizing their coordinates on the input image of interest. This is ideally achieved by labeling each pixel in an image as a backgroun…