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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7915760/ https://www.ncbi.nlm.nih.gov/pubmed/33567620 http://dx.doi.org/10.3390/s21041191 |