Development of a Modified CycleGAN Model with Residual Blocks and Perceptual Loss for Image Dehazing

Fog reduces image contrast and clarity, creating challenges for applications such as autonomous driving and remote sensing. This study proposes a series of CycleGAN modifications for single image dehazing using unpaired data, integrating residual blocks, attention mechanisms, VGG19-based perceptual...

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Autores principales:	Sani Moch Sopian, Arief Suryadi Satyawan, Mokhammad Mirza Etnisa Haqiqi, Helfy Susilawati, Beni Wijaya, Khaulyca Arva Artemysia, Firman, Muhammad Ikbal Samie
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Center for Research and Community Service, Institut Informatika Indonesia Surabaya 2025-07-01
Colección:	Teknika
Materias:	Dehazing CycleGAN Deep Learning Residual Block Attention Mechanism
Acceso en línea:	https://ejournal.ikado.ac.id/index.php/teknika/article/view/1235
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