Semantic Scholar Open Access 2021 91 sitasi

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

Giovanna Castellano G. Vessio

Abstrak

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.

Topik & Kata Kunci

Penulis (2)

G

Giovanna Castellano

G

G. Vessio

Format Sitasi

Castellano, G., Vessio, G. (2021). Deep learning approaches to pattern extraction and recognition in paintings and drawings: an overview. https://doi.org/10.1007/s00521-021-05893-z

Akses Cepat

Lihat di Sumber doi.org/10.1007/s00521-021-05893-z
Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
91×
Sumber Database
Semantic Scholar
DOI
10.1007/s00521-021-05893-z
Akses
Open Access ✓