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» Image Based Regression Using Boosting Method
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ICPR
2006
IEEE
15 years 10 months ago
Forest Extension of Error Correcting Output Codes and Boosted Landmarks
In this paper, we introduce a robust novel approach for detecting objects category in cluttered scenes by generating boosted contextual descriptors of landmarks. In particular, ou...
Oriol Pujol, Petia Radeva, Sergio Escalera
TIP
2011
137views more  TIP 2011»
14 years 4 months ago
Boosting Color Feature Selection for Color Face Recognition
—This paper introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boost...
Jae Young Choi, Yong Man Ro, Konstantinos N. Plata...
CVPR
2006
IEEE
15 years 11 months ago
Joint Boosting Feature Selection for Robust Face Recognition
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang
CLEF
2010
Springer
14 years 10 months ago
Experiences at ImageCLEF 2010 using CBIR and TBIR Mixing Information Approaches
The main goal of this paper it is to present our experiments in ImageCLEF 2010 Campaign (Wikipedia retrieval task). This edition we present a different way of using textual and vis...
Joan Benavent, Xaro Benavent, Esther de Ves, Ruben...
IJON
2007
114views more  IJON 2007»
14 years 9 months ago
Ridgelet kernel regression
In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...
Shuyuan Yang, Min Wang, Licheng Jiao