4 papers
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks
George Cann, Anthony Bourached, Ryan-Rhys Griffiths +1
We apply generative adversarial convolutional neural networks to the problem of style transfer to underdrawings and ghost-images in x-rays of fine art paintings with a special focu…
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars
Anthony Bourached, George Cann, Ryan-Rhys Griffiths +1
We describe the application of convolutional neural network style transfer to the problem of improved visualization of underdrawings and ghost-paintings in fine art oil paintings.…
Ares: A Mars model retrieval framework for ExoMars Trace Gas Orbiter NOMAD solar occultation measurements
George Cann, Ahmed Al-Refaie, Ingo Waldmann +2
Ares is an extension of the TauREx 3 retrieval framework for the Martian atmosphere. Ares is a collection of new atmospheric parameters and forward models, designed for the Europea…
Raiders of the Lost Art
Anthony Bourached, George Cann
Neural style transfer, first proposed by Gatys et al. (2015), can be used to create novel artistic work through rendering a content image in the form of a style image. We present a…