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Extra Proximal-Gradient Network with Learned Regularization for Image Compressive Sensing Reconstruction
Learned optimization algorithms are promising approaches to inverse problems by leveraging advanced numerical optimization schemes and deep neural network techniques in machine learning. In this paper, we propose a novel deep neural network architecture imitating an extra proximal gradient algorithm...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9319865/ https://www.ncbi.nlm.nih.gov/pubmed/35877622 http://dx.doi.org/10.3390/jimaging8070178 |