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A Generative Adversarial Network-Based Image Denoiser Controlling Heterogeneous Losses

We propose a novel generative adversarial network (GAN)-based image denoising method that utilizes heterogeneous losses. In order to improve the restoration quality of the structural information of the generator, the heterogeneous losses, including the structural loss in addition to the conventional...

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Detalhes bibliográficos
Publicado no:Sensors (Basel)
Main Authors: Cho, Sung In, Park, Jae Hyeon, Kang, Suk-Ju
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI 2021
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7915760/
https://ncbi.nlm.nih.gov/pubmed/33567620
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s21041191
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