PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Machine Learning Approach for Material Detection in Hyperspectral Images
Raphaël Marée, Benjamin Stevens, Pierre Geurts, Yves Guern and Philippe Mack
Proc. 6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum (CVPR09) 2009.

Abstract

In this paper we propose a machine learning approach for the detection of gaseous traces in thermal infra red hyperspectral images. It exploits both spectral and spatial information by extracting subcubes and by using extremely randomized trees with multiple outputs as a classifier. Promising results are shown on a dataset of more than 60 hypercubes.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:6033
Deposited By:Pierre Geurts
Deposited On:08 March 2010