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» Learning Visual Invariance
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CVPR
2011
IEEE
13 years 3 months ago
Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation
From conventional wisdom and empirical studies of annotated data, it has been shown that visual statistics such as object frequencies and segment sizes follow power law distributi...
Alex Shyr, Trevor Darrell, Michael Jordan, Raquel ...
IJNSEC
2010
141views more  IJNSEC 2010»
13 years 2 months ago
Protection of an Intrusion Detection Engine with Watermarking in Ad Hoc Networks
In this paper we present an intrusion detection engine comprised of two main elements; firstly, a neural network for the actual detection task and secondly watermarking techniques...
Aikaterini Mitrokotsa, Nikos Komninos, Christos Do...
JMLR
2010
367views more  JMLR 2010»
13 years 2 months ago
Locally Linear Denoising on Image Manifolds
We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...
Dian Gong, Fei Sha, Gérard G. Medioni
JMLR
2010
139views more  JMLR 2010»
13 years 2 months ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
AGI
2011
12 years 11 months ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia