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NPL
2002
168views more  NPL 2002»
13 years 4 months ago
Reduced Rank Kernel Ridge Regression
Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...
Gavin C. Cawley, Nicola L. C. Talbot
IGARSS
2010
13 years 2 months ago
Support vector machines regression for estimation of forest parameters from airborne laser scanning data
Estimation of forest stand parameters from airborne laser scanning data relies on the selection of laser metrics sets and numerous field plots for model calibration. In mountainou...
Jean-Matthieu Monnet, Frédéric Berge...
JEI
2010
123views more  JEI 2010»
12 years 11 months ago
Estimating reflectance from multispectral camera responses based on partial least-squares regression
Abstract. In multispectral imaging systems, the accuracy of reflectance estimation can be degraded by the nonlinearity in imaging process, which is due to non-Gaussian distribution...
Hui-Liang Shen, Hui-Jiang Wan, Zhe-Chao Zhang
WSC
2004
13 years 6 months ago
Teaching Regression with Simulation
Computer simulations can be used to teach complicated statistical concepts in linear regression more quickly and effectively than traditional lecture alone. In introductory applie...
John H. Walker
ICCV
2011
IEEE
12 years 4 months ago
Regression from Local Features for Viewpoint and Pose Estimation
In this paper we propose a framework for learning a regression function form a set of local features in an image. The regression is learned from an embedded representation that re...
Marwan Torki, Ahmed Elgammal