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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… 
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Artificial neural networkComputer scienceConvolutional neural networkDeep learning

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… 
2018
2018
Singer Recognition Based on Convolutional Deep Belief Networks
  • Yang LiC. Li
  • IOP Conference Series: Materials Science and…
  • 2018
  • Corpus ID: 69545521
Singer recognition is an important branch of music retrieval and classification. This paper focuses on the application of… 
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… 
2016
2016
Keyword Spotting with Convolutional Deep Belief Networks and Dynamic Time Warping
To spot keywords on handwritten documents, we present a hybrid keyword spotting system, based on features extracted with… 
2016
2016
Efficient deep learning of 3D structural brain MRIs for manifold learning and lesion segmentation with application to multiple sclerosis
Deep learning methods have shown great success in many research areas such as object recognition, speech recognition, and natural… 
2014
2014
Convolutional Data : Towards Deep Audio Learning from Big Data ( Abstract )
Deep Learning has become a popular approach for unsupervised feature learning [3]. It is now used extensively for object, face… 
2014
2014
Unsupervised feature learning on monaural DOA estimation using convolutional deep belief networks
In recent years, deep learning approaches have gained significant interest as a way of building hierarchical representations from… 
2011
2011
Report on Challenge for summer internship at DiCarlo Lab , MIT : Convolutional Deep Belief Networks in Python
An object oriented design was employed for the project. This significantly improves the readability and scalability of the code… 
2010
2010
Learning and Invariance in a Family of Hierarchical Kernels
Understanding invariance and discrimination properties of hierarchical models is arguably the key to understanding how and why… 
2010
2010
Applying Deep Belief Networks to the Game of Go a Capstone Experience Manuscript Presented By
Title: Applying Deep Belief Networks in the Game of Go Author: Peter Krafft, Mathematics and Statistics CE Type: Independent… 
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