34 citations · 34 across the 2 of their papers we have counts for
6 papers
Overt visual attention on rendered 3D objects
Oleksii Sidorov, Joshua S. Harvey, Hannah E. Smithson +1
This work covers multiple aspects of overt visual attention on 3D renders: measurement, projection, visualization, and application to studying the influence of material appearance…
Craquelure as a Graph: Application of Image Processing and Graph Neural Networks to the Description of Fracture Patterns
Oleksii Sidorov, Jon Yngve Hardeberg
Cracks on a painting is not a defect but an inimitable signature of an artwork which can be used for origin examination, aging monitoring, damage identification, and even forgery d…
Hyperspectral Calibration of Art: Acquisition and Calibration Workflows
Ruven Pillay, Jon Y Hardeberg, Sony George
Hyperspectral imaging has become an increasingly used tool in the analysis of works of art. However, the quality of the acquired data and the processing of that data to produce acc…
Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution
Oleksii Sidorov, Jon Yngve Hardeberg
Deep learning algorithms have demonstrated state-of-the-art performance in various tasks of image restoration. This was made possible through the ability of CNNs to learn from larg…
Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification
Tomáš Majtner, Buda Bajić, Sule Yildirim +3
In this report, we are presenting our automated prediction system for disease classification within dermoscopic images. The proposed solution is based on deep learning, where we em…
A bag-to-class divergence approach to multiple-instance learning
Kajsa Møllersen, Jon Yngve Hardeberg, Fred Godtliebsen
In multi-instance (MI) learning, each object (bag) consists of multiple feature vectors (instances), and is most commonly regarded as a set of points in a multidimensional space. A…