Artificial Neural Networks and Deep Learning in the Visual Arts: a review
| Autor: | Adrian Carballal, Iria Santos, Nereida Rodriguez-Fernandez, Luz Castro, Alvaro Torrente-Patiño |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Artificial neural network Computer science business.industry Deep learning 02 engineering and technology Visual arts Identification (information) 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Table (database) 020201 artificial intelligence & image processing Artificial intelligence business Software |
| Zdroj: | Neural Computing and Applications. 33:121-157 |
| ISSN: | 1433-3058 0941-0643 |
| DOI: | 10.1007/s00521-020-05565-4 |
| Popis: | In this article, we perform an exhaustive analysis of the use of Artificial Neural Networks and Deep Learning in the Visual Arts. We begin by introducing changes in Artificial Intelligence over the years and examine in depth the latest work carried out in prediction, classification, evaluation, generation, and identification through Artificial Neural Networks for the different Visual Arts. While we highlight the contributions of photography and pictorial art, there are also other uses for 3D modeling, including video games, architecture, and comics. The results of the investigations discussed show that the use of Artificial Neural Networks in the Visual Arts continues to evolve and have recently experienced significant growth. To complement the text, we include a glossary and table with information about the most commonly employed image datasets. |
| Databáze: | OpenAIRE |
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