Speeding up convolutional neural networks with low rank expansions
The focus of this paper is speeding up the application of convolutional neural networks. While delivering impressive results across a range of computer vision and machine learning tasks, these networks are computationally demanding, limiting their deployability. Convolutional layers generally consum...
Principais autores: | Jaderberg, M, Vedaldi, A, Zisserman, A |
---|---|
Formato: | Conference item |
Publicado em: |
BMVA Press
2014
|
Registros relacionados
-
Speeding up convolutional neural networks with low rank expansions
por: Jaderberg, M, et al.
Publicado em: (2014) -
Reading text in the wild with convolutional neural networks
por: Jaderberg, M, et al.
Publicado em: (2014) -
Reading text in the wild with convolutional neural networks
por: Jaderberg, M, et al.
Publicado em: (2015) -
Synthetic data and artificial neural networks for natural scene text recognition
por: Jaderberg, M, et al.
Publicado em: (2014) -
Synthetic data and artificial neural networks for natural scene text recognition
por: Jaderberg, M, et al.
Publicado em: (2014)