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PAMI
2008
119views more  PAMI 2008»
13 years 8 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
ICCV
2005
IEEE
14 years 10 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
IEEEPACT
2005
IEEE
14 years 2 months ago
A Simple Divide-and-Conquer Approach for Neural-Class Branch Prediction
The continual demand for greater performance and growing concerns about the power consumption in highperformance microprocessors make the branch predictor a critical component of ...
Gabriel H. Loh
JMLR
2010
143views more  JMLR 2010»
13 years 3 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
TNN
2008
114views more  TNN 2008»
13 years 8 months ago
Relevance-Based Feature Extraction for Hyperspectral Images
Abstract--Hyperspectral imagery affords researchers all discriminating details needed for fine delineation of many material classes. This delineation is essential for scientific re...
Michael J. Mendenhall, Erzsébet Meré...