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» Probabilistic Scene Models for Image Interpretation
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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...
ICCV
1999
IEEE
15 years 2 months ago
Learning Low-Level Vision
We describe a learning-based method for low-level vision problems--estimating scenes from images. We generate a synthetic world of scenes and their corresponding rendered images, m...
William T. Freeman, Egon C. Pasztor
CORIA
2010
14 years 4 months ago
Spatio-Temporal Modeling for Knowledge Discovery in Satellite Image Databases
Knowledge discovery from satellite images in spatio-temporal context remains one of the major challenges in the remote sensing field. It is, always, difficult for a user to manuall...
Wadii Boulila, Imed Riadh Farah, Karim Saheb Ettab...
CIVR
2004
Springer
194views Image Analysis» more  CIVR 2004»
15 years 3 months ago
A Test-Bed for Region-Based Image Retrieval Using Multiple Segmentation Algorithms and the MPEG-7 eXperimentation Model: The Sch
The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a referenc...
Vasileios Mezaris, Haralambos Doulaverakis, Raul M...
DICTA
2007
14 years 11 months ago
The Tower of Knowledge Scheme for Learning in Computer Vision
A scheme, named tower of knowledge (ToK), is proposed for interpreting 3D scenes. The ToK encapsulates causal dependencies between object appearance and functionality. We demonstr...
Maria Petrou, Mai Xu