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» Pruning Training Sets for Learning of Object Categories
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ECCV
2006
Springer
14 years 11 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn
GECCO
2004
Springer
107views Optimization» more  GECCO 2004»
14 years 2 months ago
Multiple Species Weighted Voting - A Genetics-Based Machine Learning System
Multiple Species Weighted Voting (MSWV) is a genetics-based machine learning (GBML) system with relatively few parameters that combines N two-class classifiers into an N -class cla...
Alexander F. Tulai, Franz Oppacher
NN
2002
Springer
125views Neural Networks» more  NN 2002»
13 years 8 months ago
Generalized relevance learning vector quantization
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
Barbara Hammer, Thomas Villmann
HRI
2009
ACM
14 years 3 months ago
Learning about objects with human teachers
A general learning task for a robot in a new environment is to learn about objects and what actions/effects they afford. To approach this, we look at ways that a human partner c...
Andrea Lockerd Thomaz, Maya Cakmak
CGF
2008
192views more  CGF 2008»
13 years 9 months ago
Non-Rigid Registration Under Isometric Deformations
We present a robust and efficient algorithm for the pairwise non-rigid registration of partially overlapping 3D surfaces. Our approach treats non-rigid registration as an optimiza...
Qi-Xing Huang, Bart Adams, Martin Wicke, Leonidas ...