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» Adapting Visual Category Models to New Domains
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ICCV
2003
IEEE
15 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
68
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EMNLP
2008
14 years 11 months ago
Adapting a Lexicalized-Grammar Parser to Contrasting Domains
Most state-of-the-art wide-coverage parsers are trained on newspaper text and suffer a loss of accuracy in other domains, making parser adaptation a pressing issue. In this paper ...
Laura Rimell, Stephen Clark
CVPR
2010
IEEE
14 years 9 months ago
Attribute-centric recognition for cross-category generalization
We propose an approach to find and describe objects within broad domains. We introduce a new dataset that provides annotation for sharing models of appearance and correlation acr...
Ali Farhadi, Ian Endres, Derek Hoiem
ICASSP
2010
IEEE
14 years 9 months ago
Adaptive compressed sensing - A new class of self-organizing coding models for neuroscience
Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. Ho...
William K. Coulter, Cristopher J. Hillar, Guy Isle...
ENTCS
2008
99views more  ENTCS 2008»
14 years 9 months ago
Visual Specification of Metrics for Domain Specific Visual Languages
We present a Domain Specific Visual Language (DSVL) for the definition of metrics for other DSVLs. The metrics language has been defined using meta-modelling, and includes some of...
Esther Guerra, Paloma Díaz, Juan de Lara