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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…
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…
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…
Dataset Cleaning -- A Cross Validation Methodology for Large Facial Datasets using Face Recognition
Viktor Varkarakis, Peter Corcoran
In recent years, large "in the wild" face datasets have been released in an attempt to facilitate progress in tasks such as face detection, face recognition, and other tasks. Most…
Advanced Deep Learning Methodologies for Skin Cancer Classification in Prodromal Stages
Muhammad Ali Farooq, Asma Khatoon, Viktor Varkarakis +1
Technology-assisted platforms provide reliable solutions in almost every field these days. One such important application in the medical field is the skin cancer classification in…
Towards Unconstrained Palmprint Recognition on Consumer Devices: a Literature Review
Adrian-S. Ungureanu, Saqib Salahuddin, Peter Corcoran
As a biometric palmprints have been largely under-utilized, but they offer some advantages over fingerprints and facial biometrics. Recent improvements in imaging capabilities on h…