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» Resampling methods for input modeling
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PRL
2011
14 years 9 months ago
Consistency of functional learning methods based on derivatives
In some real world applications, such as spectrometry, functional models achieve better predictive performances if they work on the derivatives of order m of their inputs rather t...
Fabrice Rossi, Nathalie Villa-Vialaneix
140
Voted
ICPR
2000
IEEE
16 years 3 months ago
A Quick 3D-2D Registration Method for a Wide-Range of Applications
Amethod for quick determination of the position and pose of a 3D free-form object with respect to its 2D projective image(s) is proposed. It is a precondition of the method that a...
Yasuyo Kita, Nobuyuki Kita, Dale L. Wilson, J. Ali...
148
Voted
ICPR
2008
IEEE
15 years 9 months ago
Flexible object recognition in cluttered scenes using relative point distribution models
This paper introduces an edge-based object recognition method that is robust with respect to clutter, occlusion and object deformations. The method combines the use of local featu...
Alexandros Bouganis, Murray Shanahan
138
Voted
CVPR
2008
IEEE
16 years 4 months ago
Visibility in bad weather from a single image
Bad weather, such as fog and haze, can significantly degrade the visibility of a scene. Optically, this is due to the substantial presence of particles in the atmosphere that abso...
Robby T. Tan
116
Voted
ASWEC
2007
IEEE
15 years 6 months ago
Managing Conflicts When Using Combination Strategies to Test Software
Testers often represent systems under test in input parameter models. These contain parameters with associated values. Combinations of parameter values, with one value for each pa...
Mats Grindal, Jeff Offutt, Jonas Mellin