Cargando…
Film and Video Quality Optimization Using Attention Mechanism-Embedded Lightweight Neural Network Model
In filming, the collected video may be blurred due to camera shake and object movement, causing the target edge to be unclear or deforming the targets. In order to solve these problems and deeply optimize the quality of movie videos, this work proposes a video deblurring (VD) algorithm based on neur...
Autor principal: | Ma, Youwen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200523/ https://www.ncbi.nlm.nih.gov/pubmed/35720938 http://dx.doi.org/10.1155/2022/8229580 |
Ejemplares similares
-
Retracted: Film and Video Quality Optimization Using Attention Mechanism-Embedded Lightweight Neural Network Model
por: Intelligence and Neuroscience, Computational
Publicado: (2023) -
A Lightweight Recurrent Grouping Attention Network for Video Super-Resolution
por: Zhu, Yonggui, et al.
Publicado: (2023) -
Lightweight and efficient neural network with SPSA attention for wheat ear detection
por: Dong, Yan, et al.
Publicado: (2022) -
Automatic Recognition of Road Damage Based on Lightweight Attentional Convolutional Neural Network
por: Liang, Han, et al.
Publicado: (2022) -
Driving Behavior Recognition Algorithm Combining Attention Mechanism and Lightweight Network
por: Wang, Lili, et al.
Publicado: (2022)