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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… Expand
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Papers overview

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2018
2018
Collective endeavours in the fields of computational neuroscience, software engineering, and biology permitted outlining… Expand
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2017
2017
Understanding visual input as perceived by humans is a challenging task for machines. Today, most successful methods work by… Expand
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Highly Cited
2014
Highly Cited
2014
  • Yuanfang Ren, Yan Wu
  • International Joint Conference on Neural Networks…
  • 2014
  • Corpus ID: 5868677
In recent years, deep learning approaches have been successfully used to learn hierarchical representations of image data, audio… Expand
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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… Expand
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Highly Cited
2011
Highly Cited
2011
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks (DBNs… Expand
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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… Expand
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Highly Cited
2010
Highly Cited
2010
Convolutional neural networks (CNNs) have been successfully applied to many tasks such as digit and object recognition. Using… Expand
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Highly Cited
2009
Highly Cited
2009
In recent years, deep learning approaches have gained significant interest as a way of building hierarchical representations from… Expand
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Highly Cited
2009
Highly Cited
2009
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling… Expand
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Highly Cited
2009
Highly Cited
2009
For many pattern recognition tasks, the ideal input feature would be invariant to multiple confounding properties (such as… Expand
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