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» On Discriminative Semi-Supervised Classification
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ICCV
2005
IEEE
14 years 11 months ago
Modeling Scenes with Local Descriptors and Latent Aspects
We present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. Our formulation provides answers to...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...
ICPR
2008
IEEE
14 years 10 months ago
Weakly supervised learning using proportion-based information: An application to fisheries acoustics
This paper addresses the inference of probabilistic classification models using weakly supervised learning. In contrast to previous work, the use of proportion-based training data...
Carla Scalarin, Jacques Masse, Jean-Marc Boucher, ...
MICCAI
2005
Springer
14 years 10 months ago
Exploiting Temporal Information in Functional Magnetic Resonance Imaging Brain Data
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, Ne...
CLASSIFICATION
2006
108views more  CLASSIFICATION 2006»
13 years 9 months ago
The Practice of Cluster Analysis
Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Jon R. Kettenring
VLSISP
2010
254views more  VLSISP 2010»
13 years 7 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...