6 search results - page 1 / 2 » Natural Image Denoising with Convolutional Networks |
NIPS
2008
13 years 6 months ago
2008
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
ICANN
2010
Springer
13 years 5 months ago
2010
Springer
Training convolutional neural networks (CNNs) on large sets of high-resolution images is too computationally intense to be performed on commodity CPUs. Such architectures however ...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
CVPR
2004
IEEE
14 years 6 months ago
2004
IEEE
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter...
ICCV
2011
IEEE
12 years 4 months ago
2011
IEEE
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...