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» An Inference Network Approach to Image Retrieval
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81
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ICML
2009
IEEE
15 years 10 months ago
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 such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
PAMI
2012
13 years 1 days ago
Holistic Context Models for Visual Recognition
— A novel framework to context modeling, based on the probability of co-occurrence of objects and scenes is proposed. The modeling is quite simple, and builds upon the availabili...
Nikhil Rasiwasia, Nuno Vasconcelos
CJ
2010
131views more  CJ 2010»
14 years 7 months ago
Probabilistic Approaches to Estimating the Quality of Information in Military Sensor Networks
an be used to abstract away from the physical reality by describing it as components that exist in discrete states with probabilistically invoked actions that change the state. The...
Duncan Gillies, David Thornley, Chatschik Bisdikia...
74
Voted
ECCV
2000
Springer
15 years 11 months ago
Non-linear Bayesian Image Modelling
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Christopher M. Bishop, John M. Winn
VISUAL
2000
Springer
15 years 1 months ago
Statistical Motion-Based Retrieval with Partial Query
We present an original approach for motion-based retrieval involving partial query. More precisely, we propose an uni ed statistical framework both to extract entities of interest ...
Ronan Fablet, Patrick Bouthemy