DEEP LEARNING-BASED CREATION OF FRACTAL ART GRAPHICS AND FRACTAL ANALYSIS OF INFORMATION FLOW

This article discusses the creation of fractal art graphics based on deep learning technologies and the fractal analysis of information flow. The application of neural networks in the image creation process using unconventional structures of fractal geometry, along with the aesthetic and informational properties of the created graphics, is analyzed. Additionally, the methods of representing and evaluating the complex structure of information flows through fractal modeling are presented. The proposed approaches not only ensure the integration of fractal art with modern digital technologies but also serve to enhance the effectiveness of information systems. The results are presented through graphical images, statistical analyses, and visualizations, highlighting the practical importance of fractal structures in information technology. Furthermore, the article examines the role of artificial intelligence in transforming art design and education, and how deep learning opens up opportunities for developing both artistic and technical skills. The analysis of information flow during the design process is explored, shedding light on the potential of deep learning to open up new possibilities in graphic creation and improve the educational experience of students in the fields of art and design.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-25
DOI
https://doi.org/10.5281/zenodo.15284426
Primary Topic
Digital Media and Visual Art
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DEEP LEARNING-BASED CREATION OF FRACTAL ART GRAPHICS AND FRACTAL ANALYSIS OF INFORMATION FLOW

Zenodo (CERN European Organization for Nuclear Research)
Digital Media and Visual Art
article

DEEP LEARNING-BASED CREATION OF FRACTAL ART GRAPHICS AND FRACTAL ANALYSIS OF INFORMATION FLOW

article en

Abstract

This article discusses the creation of fractal art graphics based on deep learning technologies and the fractal analysis of information flow. The application of neural networks in the image creation process using unconventional structures of fractal geometry, along with the aesthetic and informational properties of the created graphics, is analyzed. Additionally, the methods of representing and evaluating the complex structure of information flows through fractal modeling are presented. The proposed approaches not only ensure the integration of fractal art with modern digital technologies but also serve to enhance the effectiveness of information systems. The results are presented through graphical images, statistical analyses, and visualizations, highlighting the practical importance of fractal structures in information technology. Furthermore, the article examines the role of artificial intelligence in transforming art design and education, and how deep learning opens up opportunities for developing both artistic and technical skills. The analysis of information flow during the design process is explored, shedding light on the potential of deep learning to open up new possibilities in graphic creation and improve the educational experience of students in the fields of art and design.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 38%
Digital Media and Visual Art
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.