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» Boosting with Diverse Base Classifiers
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CEC
2010
IEEE
14 years 10 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
IC
2004
14 years 11 months ago
IskaWeb: A Web-Based Information System for the Classification of Industrial Wastes
Industrial wastes must be classified at least two times on the way from the owner of the waste to the waste disposal facility in order to ensure that waste handling is in conformi...
J. O. Dada, Hans-Dieter Kochs, Jörg Petersen
77
Voted
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
CNSM
2010
14 years 7 months ago
An investigation on the identification of VoIP traffic: Case study on Gtalk and Skype
The classification of encrypted traffic on the fly from network traces represents a particularly challenging application domain. Recent advances in machine learning provide the opp...
Riyad Alshammari, A. Nur Zincir-Heywood
CVPR
2001
IEEE
15 years 11 months ago
Learning Representative Local Features for Face Detection
This paper describes a face detection approach via learning local features. The key idea is that local features, being manifested by a collection of pixels in a local region, are ...
Xiangrong Chen, Lie Gu, Stan Z. Li, HongJiang Zhan...