Artificial Neural Networks and Deep Learning in Visual Arts: a Review
| UDC.coleccion | Investigación | |
| UDC.departamento | Ciencias da Computación e Tecnoloxías da Información | |
| UDC.endPage | 157 | |
| UDC.grupoInv | RNASA - IMEDIR (INIBIC) | |
| UDC.grupoInv | Tecnoloxías Creativas e Intelixencia Artificial (TCIA) | |
| UDC.institutoCentro | CITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación | |
| UDC.journalTitle | Neural Computing and Applications | |
| UDC.startPage | 121 | |
| UDC.volume | 33 | |
| dc.contributor.author | Santos, Iria | |
| dc.contributor.author | Castro, M. Luz | |
| dc.contributor.author | Rodríguez-Fernández, Nereida | |
| dc.contributor.author | Torrente-Patiño, Álvaro | |
| dc.contributor.author | Carballal, Adrián | |
| dc.date.accessioned | 2026-02-06T18:15:11Z | |
| dc.date.available | 2026-02-06T18:15:11Z | |
| dc.date.issued | 2021 | |
| dc.description | “This version of the article has been accepted for publication, after peer review but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00521-020-05565-4. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms” | |
| dc.description.abstract | [Abstract]: In this article we make an intensive analysis of the use of Artificial Neural Network and Deep Learning in Visual Arts. We introduce the content on Artificial Intelligence over the years and examine in depth the latest work carried out in prediction, classi_cation, evaluation, generation, and identification through Artifiial Neural Networks for the different Visual Arts. We highlight the contributions of photography and pictorial artworks, but there are also other uses for 3D modeling, video games, architecture, or comics. The reported results of the different investigations mentioned show us that, in the field of Visual Arts, Artificial Neural Networks continue to evolve constantly and that lately they show significant growth. To complement the text, we include a table with information about the most employed image data sets and a glossary. | |
| dc.description.sponsorship | This work has also been supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia (Ref. ED431G01, ED431D 201716), and Competitive Reference Groups (Ref. ED431C 201849). | |
| dc.description.sponsorship | Xunta de Galicia; ED431G01 | |
| dc.description.sponsorship | Xunta de Galicia; ED431D 201716 | |
| dc.description.sponsorship | Xunta de Galicia; ED431C 201849 | |
| dc.identifier.citation | Santos, I., Castro, L., Rodriguez-Fernandez, N. et al. Artificial Neural Networks and Deep Learning in the Visual Arts: a review. Neural Comput & Applic 33, 121–157 (2021). https://doi.org/10.1007/s00521-020-05565-4 | |
| dc.identifier.doi | 10.1007/s00521-020-05565-4 | |
| dc.identifier.issn | 0941-0643 | |
| dc.identifier.issn | 1433-3058 | |
| dc.identifier.uri | https://hdl.handle.net/2183/47287 | |
| dc.language.iso | eng | |
| dc.publisher | Springer Nature | |
| dc.relation.uri | https://doi.org/10.1007/s00521-020-05565-4 | |
| dc.rights.accessRights | open access | |
| dc.subject | Artificial Neural Networks | |
| dc.subject | Generative Adversarial Networks | |
| dc.subject | Convolutional Neural Networks | |
| dc.subject | Deep Learning | |
| dc.subject | Visual Arts | |
| dc.subject | Machine Learning | |
| dc.subject | Prediction | |
| dc.subject | Classification | |
| dc.subject | Evaluation | |
| dc.subject | Generation | |
| dc.subject | Identification | |
| dc.subject | Transfer Learning | |
| dc.subject | Datasets | |
| dc.title | Artificial Neural Networks and Deep Learning in Visual Arts: a Review | |
| dc.type | journal article | |
| dc.type.hasVersion | AM | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 4b05c41f-26dc-44a6-8928-adf2847aae27 | |
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| relation.isAuthorOfPublication | 6f70022e-b21b-4255-9693-e1402a9e4750 | |
| relation.isAuthorOfPublication.latestForDiscovery | 4b05c41f-26dc-44a6-8928-adf2847aae27 |
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