Generative adversarial network as a basis for intelligent model of imaging architectural objects based on textual description (Kemerovo, Tomsk)
Year: 2023
Type: article
Abstract: Вывод: рассматриваемая автоматизирующая система позволит существенно сократить временные, человеческие и денежные ресурсы, требуемые для разработки проекта будущего здания. Перенести в английский вариант Due to the high technology integrated into a person's daily life (smart house), this topic is relevant. One of elements of generative adversarial network is robot vacuum cleaners of various surface. Difficulties caused by this technique largely depend on the environment in which it locates. Purpose: The development of the convolutional neural network concept allowing real-time distinguishing between the building interior and exterior. Practical implication: The proposed intelligent system can distinguish between the building interior and exterior, that will considerably improve the firmware performance of modern technology in both the domestic and industrial segments.
Authors: P. A. Pylov, A. V. Dyagileva, E. A. Nikolaeva, R. V. Maitak, T. A. Shalygina
Language: Russian
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4388201477