ASPECTS OF USING GENERATIVE NEURAL NETWORKS FOR DESIGN PROJECTS
DOI:
https://doi.org/10.32689/maup.it.2025.1.21Keywords:
artificial intelligence, generative neural network, architectural design, interior designAbstract
This article explores the key aspects of using neural networks in architectural and interior design. The advantages of generative adversarial networks (GANs) in this field are discussed. Based on prompts, various images of a mountain chalet and its interior design were generated. Seamless textures were also created using the Midjourney neural network. Using the same neural network, furniture textures and posters were produced for 3D visualization of an apartment in SketchUp. This work aims to provide a comprehensive study of neural networks' application in design projects. To achieve this, it is necessary to analyze the current state of research in this field, identify the main development directions, and identify existing issues. The study describes various ways of using neural networks in architecture and interior design, evaluates the potential benefits and risks of their application, and develops recommendations for the effective use of neural networks in architectural and interior design practice. Methodology. The article uses theoretical methods of literature review, testing, and comprehensive analysis of the capabilities of modern neural networks, as well as empirical methods for studying the use of neural networks in design projects. Scientific novelty lies in the adaptation of modern approaches to the use of neural networks for the generation of architectural projects and interior design. Conclusions. The use of neural networks in architectural design as well as in interior and exterior design is becoming increasingly widespread. The development of generative image creation is progressing rapidly and is being actively applied in these fields. AI-based editing tools are being integrated into more and more well-known design programs and require preliminary analysis and study to develop specific recommendations for their use. This work provides a detailed analysis of future development directions of AI-based networks and proposes practical tools for their implementation.
References
Chen J., Shao Z., Cen C. et al. HyNet: A novel hybrid deep learning approach for efficient interior design texture retrieval. Multimed Tools Appl 83, 28125–28145 (2024). https://doi.org/10.1007/s11042-023-16579-0
Irbite A., Strode, A. Artificial intelligence vs designer: the impact of artificial intelligence on design practice. Society. Integration. Education. Proceedings of the International Scientific Conference, 4. 2021. 539–549. https://doi.org/10.17770/sie2021vol4.6310
Nguyen H. Impact of artificial intelligence in design [Thesis, LAB University of Applied Sciences]. Theseus. 2023. URL: https://www.theseus.fi/bitstream/handle/10024/804369/Nguyen_Hien.pdf?sequence=2&isAllowed=y
Petryna D., Kornuta V., Kornuta O. Using neural network tools to accelerate the development of Web interfaces. Information Technologies and Computer Engineering. 2024. 21(2). 42–50. https://doi.org/10.31649/1999-9941-2024-60-2-42-50
Бейнер Н. В., Бейнер П. С., Кулік М. В., Іваненко Д. С. НЕЙРОМЕРЕЖІ В АРХІТЕКТУРІ : ВІД ІДЕЇ ДО РЕАЛІЗАЦІЇ. Український журнал будівництва та архітектури. 2024. № 2 (020)
Божко Т., Ареф’єв В. Нейронні мережі як інструмент графічного дизайну. Вісник КНУКіМ. Серія: Мистецтвознавство. 2023. № 48. С. 125–135. doi:10.31866/2410-1176.48.2023.282475
Геренко С. Штучний інтелект у графічному дизайні: кейс генеративних нейромереж. Деміург: ідеї, технології, перспективи дизайну. 2024. 7(1), 78–91. https://doi.org/10.31866/2617-7951.7.1.2024.300924
Крук П., Гончаренко Т. Застосування глибокого навчання для прогнозування й автоматизації просторових рішень у дизайні інтер’єру. Управління розвитком складних систем. 2024. (58), 103–109. https://doi.org/10.32347/2412-9933.2024.58.103-109
Нейромережа Midjorney як інструмент для генерування дизайн графіки / О. В. Колісник, Р. Д. Михайлова, О. С. Береговий, В. В. Власюк, Д. В. Куровська. Art and Design. 2023. № 1 (21). С. 106–115.
Петрина Д., Корнута О. Порівняння різних версій додатку MIDJOURNEY та його використання в різних сферах створення візуального контенту. Вісник Хмельницького національного університету. Серія: Технічні науки. 2024. Том 333 № 2. c. 212–217. DOI 10.31891/2307-5732-2024-333-2-34