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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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 |