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Multi-Stage Attentive Network for Motion Deblurring via Binary Cross-Entropy Loss
In this paper, we present the multi-stage attentive network (MSAN), an efficient and good generalization performance convolutional neural network (CNN) architecture for motion deblurring. We build a multi-stage encoder–decoder network with self-attention and use the binary cross-entropy loss to trai...
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/PMC9601862/ https://www.ncbi.nlm.nih.gov/pubmed/37420434 http://dx.doi.org/10.3390/e24101414 |