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ICML
2005
IEEE
14 years 8 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
CVPR
2008
IEEE
14 years 9 months ago
Semantic-based indexing of fetal anatomies from 3-D ultrasound data using global/semi-local context and sequential sampling
The use of 3-D ultrasound data has several advantages over 2-D ultrasound for fetal biometric measurements, such as considerable decrease in the examination time, possibility of p...
Gustavo Carneiro, Fernando Amat, Bogdan Georgescu,...
PR
2010
147views more  PR 2010»
13 years 6 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
CVPR
2012
IEEE
11 years 10 months ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
BMCBI
2011
12 years 11 months ago
Fusion of metabolomics and proteomics data for biomarkers discovery: case study on the experimental autoimmune encephalomyelitis
Background: Analysis of Cerebrospinal Fluid (CSF) samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of these patholog...
Lionel Blanchet, Agnieszka Smolinska, Amos Attali,...