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DeepAI: A hybrid method of style transfer based on instance normalization and feature whitening

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  • Noor Fazilla Abd yusof

    (Fakulti Kecerdasan Buatan dan Keselamatan Siber, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.)

  • Siti Azirah Asmai

    (Fakulti Kecerdasan Buatan dan Keselamatan Siber, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.)

  • Goh Ong Sing

    (Fakulti Kecerdasan Buatan dan Keselamatan Siber, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.)

Abstract

Image style transfer has caught the interest and attention of researchers in artificial intelligence research. This emerging deep learning technique has shown impressive results for the past few years. Yet, a very limited number of application- ready platforms to leverage these image optimization techniques and visualize the artistic output. Therefore, we have developed a web-based image style transfer application - a platform for a user to experience the deep learning-based approaches to style transfer a digital image. We offered two (2) different methods for generating the style-transferred artwork. The DeepAI web application is available at the website (https://deepai.asia) which allows users to create unique artwork by embedding the style on their selected image.

Suggested Citation

  • Noor Fazilla Abd yusof & Siti Azirah Asmai & Goh Ong Sing, 2025. "DeepAI: A hybrid method of style transfer based on instance normalization and feature whitening," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(9), pages 361-374, September.
    • Handle: RePEc:bcp:journl:v:9:y:2025:issue-9:p:361-374
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