CONCEPT FORMATION IN CLOTHING DESIGN USING ARTIFICIAL INTELLIGENCE - RIABCHYKOV, MYKOLA; MYTSA, VIKTORIIA; MOVCHANIUK, ANASTASIIA (Herald of Khmelnytskyi National University. Technical sciences, 2023)
Artificial intelligence in the fashion industry has great potential for increasing production efficiency, creating personalized offers, implementing more sustainable production and reducing the negative impact on the environment. The originality of neural networks, as an analogue of the biological brain, lies in the ability to learn using examples that make up the training set.Modern artificial intelligence generators are widely used to optimize product industrialization as well as sales and customer experience. Instead, the use of artificial intelligence tools in relation to the design process is very limited. The leading brands of the fashion industry are limited to the use of such applications mainly for communication purposes.This work presents a number of services (Midjourney, Leonardo AI, Craiyon, DreamStudio, Playground AI, BlueWillow, NightCafe Creator, etc.), which can be used to generate images that can later be used to create a concept for a collection of clothing models.The differences of the process of generating a collection of clothing models using different types of neural networks from the classical approach of creating sketches of models of a clothing collection are presented. Detailed stages of creating a collection of clothing models in the Leonardo AI generative neural network environment.The collection of women's suits (jacket and pants) has been generated, edited and adjusted. The basis is classical and romantic styles. For one of the models in the collection, generation was performed based on a referent and a prompt detailing the structural elements.A number of advantages of using generators with artificial intelligence to create clothing collections or any light industry products have been established. It has been established that the successful use of AI depends on the designer's ability to effectively interact with these tools and adapt their results to their creative needs and market demands.
Keywords: artificial intelligence; generation; neural network; collection; prompt; referent