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» Building Shape Models from Lousy Data
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ICML
2005
IEEE
16 years 5 months ago
Learning discontinuities with products-of-sigmoids for switching between local models
Sensorimotor data from many interesting physical interactions comprises discontinuities. While existing locally weighted learning approaches aim at learning smooth functions, we p...
Marc Toussaint, Sethu Vijayakumar
CVPR
1998
IEEE
16 years 6 months ago
Efficient Multiple Model Recognition in Cluttered 3-D Scenes
We present a 3-D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matchin...
Andrew Edie Johnson, Martial Hebert
ICPR
2002
IEEE
15 years 9 months ago
A Fast Narrow Band Method and Its Application in Topology-Adaptive 3-D Modeling
We present a new fast method of modeling 3-D objects of arbitrary topology. The Level Set Methods have been used by many researchers to recover 3-D shapes of arbitrary topology. H...
Shuntaro Yui, Kenji Hara, Hongbin Zha, Tsutomu Has...
SIGOPSE
2004
ACM
15 years 9 months ago
Open problems in data collection networks
Research in sensor networks, continuous queries (CQ), and other domains has been motivated by powerful applications that aim to aggregate, assimilate, and interact with scores of ...
Jonathan Ledlie, Jeffrey Shneidman, Matt Welsh, Me...
PKDD
2007
Springer
193views Data Mining» more  PKDD 2007»
15 years 10 months ago
Learning Multi-dimensional Functions: Gas Turbine Engine Modeling
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...
Chris Drummond