Category: Deep Learning

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Deep Ruin: Climate Disasters in Imaginary Lands

Australia Council practice-based research + creative development support material. The themes I explore in this creative development + practice-led research proposal develop long-term artistic preoccupations I have with landscape, romanticism and data-driven art. In several interesting and important ways these themes merge in the fields of artificial intelligence and human-machine...

Hurley - Bage - Mawson, 3D Reconstruction 0

AAE: Digital Ghosts Project

The AAE Digital Ghosts project develops and implements novel techniques in Deep Learning (DL) in application to Antarctic Cultural Heritage. Recent developments in DL facilitate the automated colourisation and extraction (or recreation) of three-dimensional data from black and white source photographs. In concert with conventional 3D-modelling and animation techniques, these reveal...

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Deep Learning for Heritage Visualisation

Deep Learning can be employed in a variety of cultural heritage visualisation and reconstruction tasks. It is part of a family of machine learning approaches based upon the idea of ‘learning’ data representations through kernel-based algorithms that encode high dimensional abstractions in ‘deep’ or embedded artificial neural networks (ANNs). There...