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» Results of the KDD'99 Classifier Learning
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ICIP
2010
IEEE
13 years 7 months ago
A supervised micro-calcification detection approach in digitised mammograms
We present in this paper a supervised approach for automatic detection of micro-calcifications. The system is based on learning the different morphology of the micro-calcification...
Albert Torrent, Arnau Oliver, Xavier Lladó,...
HIS
2008
13 years 10 months ago
A Sequential Learning Resource Allocation Network for Image Processing Applications
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...
Stefan Wildermann, Jürgen Teich
ICML
2010
IEEE
13 years 10 months ago
Active Learning for Networked Data
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
Mustafa Bilgic, Lilyana Mihalkova, Lise Getoor
ICPR
2004
IEEE
14 years 10 months ago
Real-Time Face Detection Using Boosting in Hierarchical Feature Spaces
Boosting-basedmethods have recently led to the state-ofthe-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like featu...
Daniel Gatica-Perez, Dong Zhang, Stan Z. Li
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
14 years 22 days ago
Sets of receiver operating characteristic curves and their use in the evaluation of multi-class classification
Within the last two decades, Receiver Operating Characteristic (ROC) Curves have become a standard tool for the analysis and comparison of classifiers since they provide a conveni...
Stephan M. Winkler, Michael Affenzeller, Stefan Wa...