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Boosting HMMs with an application to speech recognition

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Keypoint Signatures for Fast Learning and Recognition

Pascal Fua, Vincent Lepetit, Michael Calonder

Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the training itself is usually relatively slow and performed offline. Although methods hav ...

2008

Classification with class-independent quality information for biometric verification

Krzysztof Kryszczuk

Biometric identity verification systems frequently face the challenges of non-controlled conditions of data acquisition. Under such conditions biometric signals may suffer from quality degradation due to extraneous, identity-independent factors. It has bee ...

EPFL2008

Promoting diversity in Gaussian mixture ensembles: an application to signature verification

Jonas Richiardi, Andrzej Drygajlo

Classifiers based on Gaussian mixture models are good performers in many pattern recognition tasks. Unlike decision trees, they can be described as stable classifier: a small change in the sampling of the training set will produce not a large change in the ...

Springer2008

Principled Detection-by-Classification from Multiple Views

Pascal Fua, François Fleuret, Jérôme Berclaz

Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...

2008

Principled Detection-by-classification from Multiple Views

Pascal Fua, François Fleuret, Jérôme Berclaz

Machine-learning based classification techniques have been shown to be effective at detecting objects in com- plex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically r ...

2008

Keypoint Signatures for Fast Learning and Recognition

Pascal Fua, Vincent Lepetit, Michael Calonder

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2008

Decision Tree Learning for Drools

Gizil Oguz

Decision trees can be used to represent a large number of expert system rules in a compact way. We describe machine learning algorithms for learning decision trees. We have implemented the algorithms, including bagging and boosting techniques. We have depl ...

2008

Ensembles for sequence learning

Christos Dimitrakakis

This thesis explores the application of ensemble methods to sequential learning tasks. The focus is on the development and the critical examination of new methods or novel applications of existing methods, with emphasis on supervised and reinforcement lear ...

EPFL2007

Information theoretic combination of classifiers with application to face detection

Julien Meynet

Combining several classifiers has become a very active subdiscipline in the field of pattern recognition. For years, pattern recognition community has focused on seeking optimal learning algorithms able to produce very accurate classifiers. However, empiri ...

EPFL2007

A multimodal pattern recognition framework for speaker detection

Patricia Besson

Speaker detection is an important component of a speech-based user interface. Audiovisual speaker detection, speech and speaker recognition or speech synthesis for example find multiple applications in human-computer interaction, multimedia content indexin ...

EPFL2007