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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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Artificial neural networkComputer scienceConvolutional neural networkDeep learning
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Robotic simulation of human brain using convolutional deep belief networks
Collective endeavours in the fields of computational neuroscience, software engineering, and biology permitted outlining… Expand
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2017
2017
Spiking Convolutional Deep Belief Networks
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
Convolutional deep belief networks for feature extraction of EEG signal
  • 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
Learning hierarchical representations for face verification with convolutional deep belief networks
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
Unsupervised learning of hierarchical representations with convolutional deep belief networks
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
Convolutional Deep Belief Networks on CIFAR-10
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
Tiled convolutional neural networks
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
Unsupervised feature learning for audio classification using convolutional deep belief networks
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
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
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
Measuring Invariances in Deep Networks
For many pattern recognition tasks, the ideal input feature would be invariant to multiple confounding properties (such as… Expand
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