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No-Reference Quality Assessment of In-Capture Distorted Videos

We introduce a no-reference method for the assessment of the quality of videos affected by in-capture distortions due to camera hardware and processing software. The proposed method encodes both quality attributes and semantic content of each video frame by using two Convolutional Neural Networks (C...

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Detalles Bibliográficos
Autores principales: Agarla, Mirko, Celona, Luigi, Schettini, Raimondo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321146/
https://www.ncbi.nlm.nih.gov/pubmed/34460689
http://dx.doi.org/10.3390/jimaging6080074

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