• Corpus ID: 220633047

Art Speaks Maths, Maths Speaks Art

@article{Leone2020ArtSM,
  title={Art Speaks Maths, Maths Speaks Art},
  author={Ninetta Leone and Simone Parisotto and Kasia Targonska-Hadzibabic and Spike Bucklow and Alessandro Launaro and Suzanne Reynolds and Carola-Bibiane Sch{\"o}nlieb},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.08886}
}
Our interdisciplinary team Mathematics for Applications in Cultural Heritage (MACH) aims to use mathematical research for the benefit of the arts and humanities. Our ultimate goal is to create user-friendly software toolkits for artists, art conservators and archaeologists. In order for their underlying mathematical engines and functionality to be optimised for the needs of the end users, we pursue an iterative approach based on a continuous communication between the mathematicians and the… 
1 Citations

Figures from this paper

Unsupervised Clustering of Roman Potsherds via Variational Autoencoders
TLDR
An artificial intelligence imaging solution to support archaeologists in the classification task of Roman commonware potsherds via the unsupervised hierarchical clustering of non-linear features learned in the latent space of a deep convolutional Variational Autoencoder (VAE) network is proposed.

References

SHOWING 1-10 OF 11 REFERENCES
Unveiling the invisible: mathematical methods for restoring and interpreting illuminated manuscripts
TLDR
A range of mathematical methods for digital image restoration and digital visualisation for illuminated manuscripts are discussed, which serve as an example for the possibilities mathematics and digital restoration offer as a generic and objective toolkit for the arts.
Exemplar-Based Inpainting: Technical Review and New Heuristics for Better Geometric Reconstructions
TLDR
From this analysis, three improvements over Criminisi et al. algorithm are presented and detailed: a tensor-based data term for a better selection of pixel candidates to fill in; a fast patch lookup strategy to ensure a better global coherence of the reconstruction; and a novel fast anisotropic spatial blending algorithm that reduces typical block artifacts using tensor models.
Variational Osmosis for Non-Linear Image Fusion
TLDR
Visual and quantitative comparisons to state-of-the-art approaches prove the out-performance and the flexibility of the proposed variational model for non-linear image fusion.
Sparse coding with an overcomplete basis set: A strategy employed by V1?
Content-based image retrieval tutorial
TLDR
This paper describes two fundamental yet efficient image retrieval techniques, the first being k - nearest neighbors (knn) and the second support vector machines (svm), and developed the equivalent software using the MATLAB environment in order to illustrate the techniques.
Partial Differential Equation Methods for Image Inpainting
  • C. Schönlieb
  • Art
    Cambridge monographs on applied and computational mathematics
  • 2016
TLDR
This paper presents a meta-analyses of the inpainting mechanisms of transport and diffusion in the context of higher-order PDEs, and describes the methods used to derive these mechanisms.
‘A’
  • P. Alam
  • Medicine
    Composites Engineering: An A–Z Guide
  • 2021
TLDR
A fluorescence-imaging-based endoscopic capsule that automates the detection process of colorectal cancer was designed and developed in the lab and offered great possibilities for future applicability in selective and specific detection of other fluorescently labelled cancers.
Introduction to Information Retrieval
  • R. Larson
  • Computer Science, Environmental Science
    J. Assoc. Inf. Sci. Technol.
  • 2010
TLDR
This chapter discusses Information Retrieval, the science and technology behind information retrieval and retrieval, and some of the techniques used in the retrieval of information.
âĂIJSparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1âĂİ
  • Vision Research
  • 1997
Leverhulme Trust âĂŞ Newsletter
    ...
    ...