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https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16524
Title: | Culture Reflecting Artistic Fashion Design Using Deep Learning and Assisting Custom Algorithm |
Authors: | Tilahun, Efa Abebe, Mesfin Rajesh Sharma, R Sungheetha, Akey Sengottaiayn, N |
Keywords: | Architecture Artistic Fashion Design Culture Reflecting Deep Learning Framework Generative Adversarial Networks |
Issue Date: | 2023 |
Publisher: | 2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023 Institute of Electrical and Electronics Engineers Inc. |
Citation: | pp. 1-10 |
Abstract: | Deep learning model developed for designing culture reflecting fashion. Handle image generation with complex structure and multicolored was the problem of previous works because it is difficult to implement existing deep learning framework for culture reflecting fashion design. To solve the failures of previous work, we have developed a Custom Assisting Algorithm for image feature extraction and transformation that treats content and style information or feature of image independently. Culture datasets are developed. The way of representing culture on fashion design using sketch and cultural patterns is designed and implemented. The model used sketch for fashion design like human and controlling sketch according is handled and presented. At the end results gained from proposed model are discussed and evaluation with baseline is presented. Generally, this is the first work by which culture reflecting on fashion is controlled and enabled. In proposed work sketch of an image is used to control representation of cultural heritages on fashion and to control local structure of an image and color patterns are used to control representation of other cultural elements like emotion and feelings. Using proposed custom assisting algorithm, a lot of problems could be solved since it is generic feature transformation and extraction algorithm. © 2023 IEEE. |
URI: | https://doi.org/10.1109/ICCAMS60113.2023.10525953 https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16524 |
ISBN: | 9798350317060 |
Appears in Collections: | Conference Papers |
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