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» Learning a Classification Model for Segmentation
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ICASSP
2011
IEEE
14 years 8 months ago
A fully automated 2-DE gel image analysis pipeline for high throughput proteomics
Image analysis is still considered as the bottleneck in 2D-gel based expression proteomics analysis for biomarkers discovery. We are presenting a new end-to-end image analysis pip...
Panagiotis Tsakanikas, Elias S. Manolakos
CVPR
2009
IEEE
16 years 12 months ago
Regularized Multi-Class Semi-Supervised Boosting
Many semi-supervised learning algorithms only deal with binary classification. Their extension to the multi-class problem is usually obtained by repeatedly solving a set of bina...
Amir Saffari, Christian Leistner, Horst Bischof
115
Voted
ICML
2010
IEEE
15 years 5 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
ICCV
2009
IEEE
15 years 2 months ago
Component analysis approach to estimation of tissue intensity distributions of 3D images
Many segmentation problems in medical imaging rely on accurate modeling and estimation of tissue intensity probability density functions. Gaussian mixture modeling, currently the ...
Arridhana Ciptadi, Cheng Chen, Vitali Zagorodnov
VLDB
2008
ACM
147views Database» more  VLDB 2008»
16 years 4 months ago
Providing k-anonymity in data mining
In this paper we present extended definitions of k-anonymity and use them to prove that a given data mining model does not violate the k-anonymity of the individuals represented in...
Arik Friedman, Ran Wolff, Assaf Schuster