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Hybrid Deep Learning for Face Verification Yi Sun1 1 Xiaogang Wang2,3
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Document Date: 2013-10-16 22:17:27


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File Size: 1,83 MB

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Company

NEC / Sun / LFW / X. / Z. / /

Currency

pence / /

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Event

FDA Phase / /

Facility

University of Massachusetts / The Chinese University of Hong Kong / /

IndustryTerm

n-th / deep belief networks / hybrid network / back-propagation algorithm / closed form solutions / convolutional deep belief networks / hybrid deep network / deep convolutional networks / large-scale feature search approach / hybrid convolutional network / convolutional neural network / greedy feature selection algorithm / learning algorithm / deep convolutional neural networks / deep neural networks / /

Organization

Xiaogang Wang2 / 3 Xiaoou Tang1 / 3 Department of Information Engineering / Chinese Academy of Sciences / General Research Fund / Chinese University of Hong Kong / University of Massachusetts / Amherst / Department of Electronic Engineering / Research Grants Council of the Kong Kong SAR / /

Person

Q. Yin / P. Li / Prince / D. Chen / Y. Fu / L. Wang / F. Wen / /

Position

hybrid ConvNet-RBM model for face verification / associate-predict model for face recognition / model for face / Fisher / Prince / Cao / /

Product

ConvNets / LFW / /

ProvinceOrState

Massachusetts / /

PublishedMedium

Machine Learning / /

Technology

neural network / artificial intelligence / back-propagation algorithm / Learning algorithms / greedy feature selection algorithm / Machine Learning / unrestricted protocol / /

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