BareFace Restoration: Using ResNet-34 for Makeup Removal

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dc.contributor.advisor Phan, Duy Hùng
dc.contributor.author Uông, Khánh Duy
dc.contributor.author Ngô, Sách Trung
dc.contributor.author Nguyễn, Hải Đăng
dc.date.accessioned 2024-02-23T03:12:33Z
dc.date.available 2024-02-23T03:12:33Z
dc.date.issued 2023
dc.identifier.uri http://ds.libol.fpt.edu.vn/handle/123456789/3990
dc.description.abstract We currently investigate the use of ResNet-34 as an encoder in the U-Net architecture, in the field of decoupling. This problem poses a major challenge because cosmetics obscure basic facial features, which is important in applications in many fields of security, entertainment and social networks. By effectively exploiting deep learning techniques to automatically remove makeup from facial images. The algorithm enhances the performance and feature extraction capabilities inherent in ResNet-34. Through testing, the results have shown that this new makeup removal model is very effective. It helps to remove makeup that not only simplifies the process but also contributes significantly to advancing computer vision applications. This investigation represents an important step forward in the development of smart solutions for image enhancement and potential applications. The architectural framework of U-Net with ResNet-34 as the encoder contributes significantly to achieving these advances. 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 Makeup Removal en_US
dc.subject U-Net en_US
dc.subject ResNet-34 en_US
dc.subject Res34Unet en_US
dc.title BareFace Restoration: Using ResNet-34 for Makeup Removal en_US
dc.title.alternative Phục hồi khuôn mặt tự nhiên: Sử dụng ResNet-34 để Loại bỏ Trang Điểm en_US
dc.type Thesis en_US


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