Deep learning approaches to pattern extraction and recognition in paintings and drawings: an overview

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Abstract

This paper provides an overview of some of the most relevant deep learning approaches to pattern extraction and recognition in visual arts, particularly painting and drawing. Recent advances in deep learning and computer vision, coupled with the growing availability of large digitized visual art collections, have opened new opportunities for computer science researchers to assist the art community with automatic tools to analyse and further understand visual arts. Among other benefits, a deeper understanding of visual arts has the potential to make them more accessible to a wider population, ultimately supporting the spread of culture.

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CITATION STYLE

APA

Castellano, G., & Vessio, G. (2021, October 1). Deep learning approaches to pattern extraction and recognition in paintings and drawings: an overview. Neural Computing and Applications. Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/s00521-021-05893-z

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