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» Classification of symbolic objects: A lazy learning approach
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CVPR
2007
IEEE
15 years 11 months ago
Human Detection via Classification on Riemannian Manifolds
We present a new algorithm to detect humans in still images utilizing covariance matrices as object descriptors. Since these descriptors do not lie on a vector space, well known m...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICCV
2005
IEEE
15 years 11 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ANNPR
2006
Springer
15 years 1 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...
97
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CLOR
2006
15 years 1 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
ICMCS
2005
IEEE
112views Multimedia» more  ICMCS 2005»
15 years 3 months ago
Segment-based approach to the recognition of emotions in speech
A new framework for the context and speaker independent recognition of emotions from voice, based on a richer and more natural representation of the speech signal, is proposed. Th...
Mohammad T. Shami, Mohamed S. Kamel