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156
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JCP
2008
167views more  JCP 2008»
15 years 3 months ago
Accelerated Kernel CCA plus SVDD: A Three-stage Process for Improving Face Recognition
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Ming Li, Yuanhong Hao
ML
2006
ACM
163views Machine Learning» more  ML 2006»
15 years 3 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
PAMI
2006
178views more  PAMI 2006»
15 years 3 months ago
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
Jakob J. Verbeek
126
Voted
IJCV
2007
145views more  IJCV 2007»
15 years 3 months ago
Building Outline Extraction from Digital Elevation Models Using Marked Point Processes
— This work presents an automatic algorithm for extracting vectorial land registers from altimetric data in dense urban areas. We focus on elementary shape extraction and propose...
Mathias Ortner, Xavier Descombes, Josiane Zerubia
CAGD
2005
88views more  CAGD 2005»
15 years 3 months ago
An efficient bit allocation for compressing normal meshes with an error-driven quantization
We propose a new wavelet compression algorithm based on the rate-distortion optimization for densely sampled triangular meshes. Exploiting the normal remesher of Guskov et al., th...
Frédéric Payan, Marc Antonini