368 citations · 517 across the 4 of their papers we have counts for
8 papers
PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy
Vahid Mirjalili, Sebastian Raschka, Arun Ross
Recent research has established the possibility of deducing soft-biometric attributes such as age, gender and race from an individual's face image with high accuracy. However, this…
Some Research Problems in Biometrics: The Future Beckons
Arun Ross, Sudipta Banerjee, Cunjian Chen +5
The need for reliably determining the identity of a person is critical in a number of different domains ranging from personal smartphones to border security; from autonomous vehicl…
FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers
Vahid Mirjalili, Sebastian Raschka, Arun Ross
Privacy concerns in the modern digital age have prompted researchers to develop techniques that allow users to selectively suppress certain information in collected data while allo…
ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI data
Taban Eslami, Vahid Mirjalili, Alvis Fong +2
Mental disorders such as Autism Spectrum Disorders (ASD) are heterogeneous disorders that are notoriously difficult to diagnose, especially in children. The current psychiatric dia…
Rank consistent ordinal regression for neural networks with application to age estimation
Wenzhi Cao, Vahid Mirjalili, Sebastian Raschka
In many real-world prediction tasks, class labels include information about the relative ordering between labels, which is not captured by commonly-used loss functions such as mult…
Spoofing PRNU Patterns of Iris Sensors while Preserving Iris Recognition
Sudipta Banerjee, Vahid Mirjalili, Arun Ross
The principle of Photo Response Non-Uniformity (PRNU) is used to link an image with its source, i.e., the sensor that produced it. In this work, we investigate if it is possible to…
Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifiers
Vahid Mirjalili, Sebastian Raschka, Arun Ross
Recent research has proposed the use of Semi Adversarial Networks (SAN) for imparting privacy to face images. SANs are convolutional autoencoders that perturb face images such that…
Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images
Vahid Mirjalili, Sebastian Raschka, Anoop Namboodiri +1
In this paper, we design and evaluate a convolutional autoencoder that perturbs an input face image to impart privacy to a subject. Specifically, the proposed autoencoder transform…