Neural Networks and Digital Arts: Some Reflections
by Rômulo Augusto Vieira Costa 1,* 
, Flávio Luiz Schiavoni 2
Arts Lab in Interfaces, Computers, and Everything Else – ALICE, Federal University of São João del-Rei, UFSJ,
São João del-Rei, Minas Gerais, Brazil
* Author to whom correspondence should be addressed.
Journal of Engineering Research and Sciences, Volume 1, Issue 1, Page # 10-18, 2022; DOI: 10.55708/js0101002
Keywords: Computer music, Generational art, Neural networks
Received: 20 January 2022, Revised: 25 January 2022, Accepted: 06 February 2022, Published Online: 24 February 2022
AMA Style
Costa RAV, Schiavoni FL. Neural Networks and Digital Arts: Some Reflections. Journal of Engineering Research and Sciences. 2022;1(1):10-18. DOI: 10.55708/js0101002
Chicago/Turabian Style
Costa, Rômulo Augusto Vieira, and Flávio Luiz Schiavoni. “Neural Networks and Digital Arts: Some Reflections.” Journal of Engineering Research and Sciences 1, no. 1 (2022): 10–18. DOI: 10.55708/js0101002
IEEE Style
R. A. V. Costa and F. L. Schiavoni, “Neural Networks and Digital Arts: Some Reflections,” Journal of Engineering Research and Sciences, vol. 1, no. 1, pp. 10–18, 2022. DOI: 10.55708/js0101002
The Constant advancement in the area of machine learning has unified some areas that until then di a of computing with the arts in general. With the emergence of digital art, people have become increasingly interested in the development of expressive techniques and algorithms for creating works of art, whether in the form of music, image, aesthetic artifacts, or even combinations of these forms, usually being applied in an interactive technology installation. Due to their high diversity of creation and complexity during processing, neural networks have been used to create these digital works, which present results that are difficult to reproduce by human hand and are usually presented in museums, conferences, or even at auctions, being sold at high prices. The fact that these works are gaining more and more recognition in the art scene, ended up raising some questions about authenticity and art. In this way, this work aims to address the historical context regarding the advancement of the area of machine learning, addressing the evolution of neural networks in this field, about what art would be and who would be the artist responsible for digital work, given that despite After performing a good part of the creation process, the computer does not perform the entire process, becoming dependent on the programmer, who in turn is responsible for defining parameters, techniques and, above all, concepts that will attribute all the aesthetic value to the work. From this point of view and the growing interest in the generation of art via computers, the present work presents applied research around neural network techniques and how they can be applied in artistic practice, either generating visual elements or generating visual elements or generating sound elements. Finally, perspectives for the future are presented and how this area can evolve even further.
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