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» Graph model selection using maximum likelihood
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ICPR
2006
IEEE
14 years 10 months ago
Image classification: Classifying distributions of visual features
We classify an image by generating a list of salient visual features present in the luminance channel, and matching the resulting variable-length feature list to categoryspecific ...
Prateek Sarkar
ICML
2007
IEEE
14 years 9 months ago
Sparse probabilistic classifiers
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Romain Hérault, Yves Grandvalet
IJCNN
2008
IEEE
14 years 3 months ago
A formula of equations of states in singular learning machines
Abstract— Almost all learning machines used in computational intelligence are not regular but singular statistical models, because they are nonidentifiable and their Fisher info...
Sumio Watanabe
EWCBR
2004
Springer
14 years 2 months ago
Quantifying the Ocean's CO2 Budget with a CoHeL-IBR System
By improving accuracy in the quantification of the ocean’s CO2 budget, a more precise estimation can be made of the terrestrial fraction of global CO2 budget and its subsequent e...
Juan M. Corchado, Jim Aiken, Emilio Corchado, Nath...
TIFS
2010
120views more  TIFS 2010»
13 years 3 months ago
Quantitative Structural Steganalysis of Jsteg
Quantitative steganalysis strives to estimate the change rate defined as the relative number of embedding changes introduced by steganography. In this paper, we propose two new cla...
Jan Kodovský, Jessica J. Fridrich