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» A Hierarchical Classifier Using New Support Vector Machine
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JMLR
2002
115views more  JMLR 2002»
13 years 7 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
MEDIAFORENSICS
2010
13 years 9 months ago
Detecting content adaptive scaling of images for forensic applications
Content-aware resizing methods have recently been developed, among which, seam-carving has achieved the most widespread use. Seam-carving's versatility enables deliberate obj...
Claude Fillion, Gaurav Sharma
ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Data Modeling Strategies for Imbalanced Learning in Visual Search
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...
TASE
2008
IEEE
13 years 7 months ago
An Intelligent Online Monitoring and Diagnostic System for Manufacturing Automation
Condition monitoring and fault diagnosis in modern manufacturing automation is of great practical significance. It improves quality and productivity, and prevents damage to machine...
Ming Ge, Yangsheng Xu, Ruxu Du
ESANN
2006
13 years 9 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...