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...

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Detalles Bibliográficos
Autores principales: Zhang, Qingchao, Ye, Xiaojing, Chen, Yunmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9319865/
https://www.ncbi.nlm.nih.gov/pubmed/35877622
http://dx.doi.org/10.3390/jimaging8070178

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