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» Classification of symbolic objects: A lazy learning approach
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CVPR
2007
IEEE
14 years 9 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
14 years 9 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
13 years 11 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...
CLOR
2006
13 years 11 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»
14 years 1 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