activity
20172022
most citedSmart Augmentation - Learning an Optimal Data Augmentation Strategy

439 citations · 1k across the 21 of their papers we have counts for

collaborators

22 papers

cs.CR2022★ 4 cited

Smart speaker design and implementation with biometric authentication and advanced voice interaction capability

Bharath Sudharsan, Peter Corcoran, Muhammad Intizar Ali

Advancements in semiconductor technology have reduced dimensions and cost while improving the performance and capacity of chipsets. In addition, advancement in the AI frameworks an…

cs.CV2021

Object Detection in Thermal Spectrum for Advanced Driver-Assistance Systems (ADAS)

Muhammad Ali Farooq, Peter Corcoran, Cosmin Rotariu +1

Object detection in thermal infrared spectrum provides more reliable data source in low-lighting conditions and different weather conditions, as it is useful both in-cabin and outs…

cs.CV2021★ 21 cited

Towards End-to-End Neural Face Authentication in the Wild -- Quantifying and Compensating for Directional Lighting Effects

Viktor Varkarakis, Wang Yao, Peter Corcoran

The recent availability of low-power neural accelerator hardware, combined with improvements in end-to-end neural facial recognition algorithms provides, enabling technology for on…

cs.CV2020★ 3 cited

Generating Thermal Image Data Samples using 3D Facial Modelling Techniques and Deep Learning Methodologies

Muhammad Ali Farooq, Peter Corcoran

Methods for generating synthetic data have become of increasing importance to build large datasets required for Convolution Neural Networks (CNN) based deep learning techniques for…

eess.IV2020

High-Accuracy Facial Depth Models derived from 3D Synthetic Data

Faisal Khan, Shubhajit Basak, Hossein Javidnia +2

In this paper, we explore how synthetically generated 3D face models can be used to construct a high accuracy ground truth for depth. This allows us to train the Convolutional Neur…

cs.NE2020

Re-Training StyleGAN -- A First Step Towards Building Large, Scalable Synthetic Facial Datasets

Viktor Varkarakis, Shabab Bazrafkan, Peter Corcoran

StyleGAN is a state-of-art generative adversarial network architecture that generates random 2D high-quality synthetic facial data samples. In this paper, we recap the StyleGAN arc…