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» Evaluating learning algorithms and classifiers
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ECCV
2010
Springer
13 years 10 months ago
Semantic Segmentation of Urban Scenes Using Dense Depth Maps
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Chenxi Zhang, Liang Wang, Ruigang Yang
CEC
2010
IEEE
13 years 9 months ago
Behavioral diversity measures for Evolutionary Robotics
Abstract— In Evolutionary Robotics (ER), explicitly rewarding for behavioral diversity recently revealed to generate efficient results without recourse to complex fitness funct...
Stéphane Doncieux, Jean-Baptiste Mouret
IUI
2011
ACM
12 years 12 months ago
Protractor3D: a closed-form solution to rotation-invariant 3D gestures
Protractor 3D is a gesture recognizer that extends the 2D touch screen gesture recognizer Protractor [8] to 3D gestures. It inherits many of Protractor’s desirable properties, s...
Sven G. Kratz, Michael Rohs
ICCV
2009
IEEE
15 years 2 months ago
Deformable Model Fitting with a Mixture of Local Experts
Local experts have been used to great effect for fitting deformable models to images. Typically, the best location in an image for the deformable model’s landmarks are found t...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
TSMC
1998
91views more  TSMC 1998»
13 years 8 months ago
Toward the border between neural and Markovian paradigms
— A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms si...
Piotr Wilinski, Basel Solaiman, A. Hillion, W. Cza...