Convolutional Deep Belief Networks

In computer science, Convolutional Deep Belief Network (CDBN) is a type of deep artificial neural network that is composed of multiple layers of… (More)
Wikipedia

Topic mentions per year

Topic mentions per year

2009-2017
02420092017

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
The remarkable development of deep learning in medicine and healthcare domain presents obvious privacy issues, when deep neural… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
2015
2015
Deep learning has traditionally been computationally expensive, and advances in training methods have been the prerequisite for… (More)
Is this relevant?
2014
2014
In recent years, deep learning approaches have been successfully used to learn hierarchical representations of image data, audio… (More)
  • figure 1
  • table I
  • figure 2
  • table II
Is this relevant?
Highly Cited
2012
Highly Cited
2012
Most modern face recognition systems rely on a feature representation given by a hand-crafted image descriptor, such as Local… (More)
  • figure 1
  • figure 2
  • table 1
  • figure 3
  • table 2
Is this relevant?
Highly Cited
2011
Highly Cited
2011
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks (DBNs… (More)
  • figure 4
Is this relevant?
Highly Cited
2010
Highly Cited
2010
We describe how to train a two-layer convolutional Deep Belief Network (DBN) on the 1.6 million tiny images dataset. When… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Is this relevant?
2010
2010
The human visual system can robustly recognize objects, even though a single object can project many different images onto the… (More)
  • figure 1
  • figure 2
  • table 1
  • table 2
  • table 3
Is this relevant?
Highly Cited
2009
Highly Cited
2009
In recent years, deep learning approaches have gained significant interest as a way of building hierarchical representations from… (More)
  • figure 1
  • figure 2
  • figure 3
  • table 2
  • table 4
Is this relevant?
Highly Cited
2009
Highly Cited
2009
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling… (More)
Is this relevant?
Highly Cited
2009
Highly Cited
2009
For many pattern recognition tasks, the ideal input feature would be invariant to multiple confounding properties (such as… (More)
  • figure 2
  • figure 4
  • figure 5
  • table 1
Is this relevant?