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NIPS
2008
13 years 11 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
ICCV
2003
IEEE
14 years 11 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
NIPS
2007
13 years 11 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
SMC
2007
IEEE
132views Control Systems» more  SMC 2007»
14 years 4 months ago
Disaster management model based on Modified Fuzzy Cognitive Maps
-This paper describes the use of a Fuzzy Cognitive Map (FCM) to model disaster reconstruction, based on data collected from the cities of BAM and Baravat. The extended fuzzy cognit...
Sandeep Chandana, Henry Leung, Jason Levy
ICIP
2005
IEEE
14 years 11 months ago
SAR images as mixtures of Gaussian mixtures
We consider the problem of image segmentation by clustering local histograms with parametric mixture-of-mixture models. These models represent each cluster by a single mixture mod...
Peter Orbanz, Joachim M. Buhmann