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High-accuracy facial depth models derived from 3D synthetic data
(Institute of Electrical and Electronics Engineers (IEEE), 2020-08-31)
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 Neural Networks (CNN) to solve facial depth ...
Generative Augmented Dataset and Annotation Frameworks for Artificial Intelligence (GADAFAI)
(Institute of Electrical and Electronics Engineers (IEEE), 2020-08-31)
Recent Advances in Artificial Intelligence (AI), particularly in the field of compute vision, have been driven by the availability of large public datasets. However, as AI begins to move into embedded devices there will ...
Infrared imaging for human thermography and breast tumor classification using thermal images
(Institute of Electrical and Electronics Engineers (IEEE), 2020-08-31)
Human thermography is considered to be an integral medical diagnostic tool for detecting heat patterns and measuring quantitative temperature data of the human body. It can be used in conjunction with other medical diagnostic ...
Re-training StyleGAN-A first step towards building large, scalable synthetic facial datasets
(Institute of Electrical and Electronics Engineers (IEEE), 2020-08-31)
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 architecture and training methodology and ...
Generating thermal image data samples using 3D facial modelling techniques and deep learning methodologies
(Institute of Electrical and Electronics Engineers (IEEE), 2020-05-26)
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 a wide range of computer vision applications. ...