87 citations · 96 across the 11 of their papers we have counts for
13 papers
Power Flow Analysis Using Deep Neural Networks in Three-Phase Unbalanced Smart Distribution Grids
Deepak Tiwari, Mehdi Jabbari Zideh, Veeru Talreja +3
Most power systems' approaches are currently tending towards stochastic and probabilistic methods due to the high variability of renewable sources and the stochastic nature of load…
Empirical Assessment of End-to-End Iris Recognition System Capacity
Priyanka Das, Richard Plesh, Veeru Talreja +4
Iris is an established modality in biometric recognition applications including consumer electronics, e-commerce, border security, forensics, and de-duplication of identity at a na…
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-…
Profile to Frontal Face Recognition in the Wild Using Coupled Conditional GAN
Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson +2
In recent years, with the advent of deep-learning, face recognition has achieved exceptional success. However, many of these deep face recognition models perform much better in han…
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…
PF-cpGAN: Profile to Frontal Coupled GAN for Face Recognition in the Wild
Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson +2
In recent years, due to the emergence of deep learning, face recognition has achieved exceptional success. However, many of these deep face recognition models perform relatively po…
Error-Corrected Margin-Based Deep Cross-Modal Hashing for Facial Image Retrieval
Fariborz Taherkhani, Veeru Talreja, Matthew C. Valenti +1
Cross-modal hashing facilitates mapping of heterogeneous multimedia data into a common Hamming space, which can beutilized for fast and flexible retrieval across different modaliti…
Zero-Shot Deep Hashing and Neural Network Based Error Correction for Face Template Protection
Veeru Talreja, Matthew C. Valenti, Nasser M. Nasrabadi
In this paper, we present a novel architecture that integrates a deep hashing framework with a neural network decoder (NND) for application to face template protection. It improves…
Attribute-Guided Coupled GAN for Cross-Resolution Face Recognition
Veeru Talreja, Fariborz Taherkhani, Matthew C Valenti +1
In this paper, we propose a novel attribute-guided cross-resolution (low-resolution to high-resolution) face recognition framework that leverages a coupled generative adversarial n…
Learning to Authenticate with Deep Multibiometric Hashing and Neural Network Decoding
Veeru Talreja, Sobhan Soleymani, Matthew C. Valenti +1
In this paper, we propose a novel multimodal deep hashing neural decoder (MDHND) architecture, which integrates a deep hashing framework with a neural network decoder (NND) to crea…
Using Deep Cross Modal Hashing and Error Correcting Codes for Improving the Efficiency of Attribute Guided Facial Image Retrieval
Veeru Talreja, Fariborz Taherkhani, Matthew C. Valenti +1
With benefits of fast query speed and low storage cost, hashing-based image retrieval approaches have garnered considerable attention from the research community. In this paper, we…
Biometrics-as-a-Service: A Framework to Promote Innovative Biometric Recognition in the Cloud
Veeru Talreja, Terry Ferrett, Matthew C. Valenti +1
Biometric recognition, or simply biometrics, is the use of biological attributes such as face, fingerprints or iris in order to recognize an individual in an automated manner. A ke…
Multibiometric Secure System Based on Deep Learning
Veeru Talreja, Matthew C. Valenti, Nasser M. Nasrabadi
In this paper, we propose a secure multibiometric system that uses deep neural networks and error-correction coding. We present a feature-level fusion framework to generate a secur…