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PAMI
2008
175views more  PAMI 2008»
13 years 4 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...
ICASSP
2010
IEEE
13 years 5 months ago
Boosted binary features for noise-robust speaker verification
The standard approach to speaker verification is to extract cepstral features from the speech spectrum and model them by generative or discriminative techniques. We propose a nov...
Anindya Roy, Mathew Magimai-Doss, Sébastien...
ICASSP
2011
IEEE
12 years 8 months ago
Online feature selection and classification
This paper presents an online feature selection and classification algorithm. The algorithm is implemented for impact acoustics signals to sort hazelnut kernels. The classifier, w...
Habil Kalkan, Bayram Cetisli
TKDE
2008
115views more  TKDE 2008»
13 years 4 months ago
A Niching Memetic Algorithm for Simultaneous Clustering and Feature Selection
Clustering is inherently a difficult task and is made even more difficult when the selection of relevant features is also an issue. In this paper, we propose an approach for simult...
Weiguo Sheng, Xiaohui Liu, Michael C. Fairhurst
ANNPR
2006
Springer
13 years 8 months ago
Visual Classification of Images by Learning Geometric Appearances Through Boosting
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...