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Clothes Design utilizing Generative AI

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dc.contributor.advisor Lương, Trung Kiên
dc.contributor.author Nguyễn, Quang Phước
dc.contributor.author Nguyễn, Ngọc Minh
dc.date.accessioned 2024-02-23T03:18:05Z
dc.date.available 2024-02-23T03:18:05Z
dc.date.issued 2023
dc.identifier.uri http://ds.libol.fpt.edu.vn/handle/123456789/3992
dc.description.abstract The dynamic domain of text-to-image generation has witnessed remarkable advancements in recent years, particularly in applications like fashion design and artistic creation, where AI algorithms have demonstrated their capabilities. In addressing the intrinsic challenge of acquiring well-labeled datasets for training, we embraced a framework outlined in [7]. This framework hinges on the collaboration of two pivotal models: the Prior Model and the Decoder. Through careful curation of publicly available datasets, we meticulously prepared datasets for both pre-training and fine-tuning phases, with a deliberate choice of the MS-COCO dataset owing to its suitability and content integrity. Our efforts lay in the development of a comprehensive pipeline for text-to-image generation, complemented by a demo for deploying a model API. This demonstrated the potential of our approach in establishing a user-friendly service for designing Print On Demand images. The efforts not only showcase the current state-of-the-art in AI-driven image generation but also position our framework as a practical and accessible solution for users seeking personalized and creative image design experiences. en_US
dc.language.iso en en_US
dc.publisher FPTU Hà Nội en_US
dc.subject Trí tuệ nhân tạo en_US
dc.subject Artificial Intelligence en_US
dc.subject Text-to-image en_US
dc.subject Shifted Diffusion en_US
dc.subject Clothes design en_US
dc.subject Print On Demand en_US
dc.subject Shirts en_US
dc.title Clothes Design utilizing Generative AI en_US
dc.title.alternative Thiết kế Trang phục ứng dụng Trí tuệ Nhân tạo Sinh en_US
dc.type Thesis en_US


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