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» Learning Models for Object Recognition
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MCS
2007
Springer
14 years 4 months ago
Group-Induced Vector Spaces
The strength of classifier combination lies either in a suitable averaging over multiple experts/sources or in a beneficial integration of complementary approaches. In this paper...
Manuele Bicego, Elzbieta Pekalska, Robert P. W. Du...
ICRA
2009
IEEE
208views Robotics» more  ICRA 2009»
13 years 8 months ago
Affordance based word-to-meaning association
Abstract-- This paper presents a method to associate meanings to words in manipulation tasks. We base our model on an affordance network, i.e., a mapping between robot actions, rob...
Verica Krunic, Giampiero Salvi, Alexandre Bernardi...
ICCV
2005
IEEE
14 years 3 months ago
Non-Negative Lighting and Specular Object Recognition
Recognition of specular objects is particularly difficult because their appearance is much more sensitive to lighting changes than that of Lambertian objects. We consider an appr...
Sameer Shirdhonkar, David W. Jacobs
ICRA
2010
IEEE
153views Robotics» more  ICRA 2010»
13 years 8 months ago
High-speed 3D object recognition using additive features in a linear subspace
— In this paper we propose a method of high-speed 3D object recognition using linear subspace method and our 3D features. This method can be applied to partial models with any si...
Asako Kanezaki, Hideki Nakayama, Tatsuya Harada, Y...
ICALT
2005
IEEE
14 years 3 months ago
Concept Maps and Learning Objects
Concept Maps constitute one of the tools mostly used in learning management due to the possibility that they offer to contextualize learning, share knowledge and for learning to le...
Leonel Iriarte Navarro, Manuel Marco Such, Daniel ...