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» Multiclass boosting with repartitioning
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PRL
2007
166views more  PRL 2007»
13 years 7 months ago
Boosted Landmarks of Contextual Descriptors and Forest-ECOC: A novel framework to detect and classify objects in cluttered scene
In this paper, we present a novel methodology to detect and recognize objects in cluttered scenes by proposing boosted contextual descriptors of landmarks in a framework of multi-...
Sergio Escalera, Oriol Pujol, Petia Radeva
ICPR
2006
IEEE
14 years 8 months ago
Forest Extension of Error Correcting Output Codes and Boosted Landmarks
In this paper, we introduce a robust novel approach for detecting objects category in cluttered scenes by generating boosted contextual descriptors of landmarks. In particular, ou...
Oriol Pujol, Petia Radeva, Sergio Escalera
JMLR
2002
144views more  JMLR 2002»
13 years 7 months ago
Round Robin Classification
In this paper, we discuss round robin classification (aka pairwise classification), a technique for handling multi-class problems with binary classifiers by learning one classifie...
Johannes Fürnkranz
CVPR
2004
IEEE
14 years 9 months ago
Asymmetrically Boosted HMM for Speech Reading
Speech reading, also known as lip reading, is aimed at extracting visual cues of lip and facial movements to aid in recognition of speech. The main hurdle for speech reading is th...
Pei Yin, Irfan A. Essa, James M. Rehg
COLT
2003
Springer
14 years 1 months ago
Learning with Equivalence Constraints and the Relation to Multiclass Learning
Abstract. We study the problem of learning partitions using equivalence constraints as input. This is a binary classification problem in the product space of pairs of datapoints. ...
Aharon Bar-Hillel, Daphna Weinshall