Enhancing Negative Film Colorization through Systematic CycleGAN Architectural Modifications: A Comprehensive Analysis of Generator and Discriminator Performance

Enhancing Negative Film Colorization through Systematic CycleGAN Architectural Modifications: A Comprehensive Analysis of Generator and Discriminator Performance

This research addresses the urgent need for deep learning-based negative film colorization technology through systematic modifications to the CycleGAN architecture. Unlike conventional approaches that focus on colorizing black-and- white images, this study targets the conversion of digitized negativ...

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Bibliographic Details
Main Authors: Khaulyca Arva Artemysia Khaulyca, Arief Suryadi Satyawan Arief, Mokhammad Mirza Etnisa Haqiqi Mirza, Helfy Susilawati Helfy, Beni Wijaya Beni, Sani Moch Sopian Sani, Muhammad Ikbal Shamie Ikbal, Firman Firman
Format: Article
Language:English
Published: Politeknik Negeri Batam 2025-06-01
Series:Journal of Applied Informatics and Computing
Subjects:
negative film colorization
cyclegan
architectural modifications
image processing
generative adversarial networks
Online Access:https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/9553
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https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/9553

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