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» Randomized Clustering Forests for Image Classification
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ACCV
2009
Springer
13 years 9 months ago
Semantic Classification in Aerial Imagery by Integrating Appearance and Height Information
Abstract. In this paper we present an efficient technique to obtain accurate semantic classification on the pixel level capable of integrating various modalities, such as color, ed...
Stefan Kluckner, Thomas Mauthner, Peter M. Roth, H...
BMCBI
2010
118views more  BMCBI 2010»
13 years 5 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
TMM
2010
231views Management» more  TMM 2010»
12 years 11 months ago
Real-Time Visual Concept Classification
As datasets grow increasingly large in content-based image and video retrieval, computational efficiency of concept classification is important. This paper reviews techniques to ac...
Jasper R. R. Uijlings, Arnold W. M. Smeulders, Rem...
CVPR
2007
IEEE
14 years 7 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs
CVPR
2010
IEEE
14 years 1 months ago
Fast and Robust Object Segmentation with the Integral Linear Classifier
We propose an efficient method, built on the popular Bag of Features approach, that obtains robust multiclass pixellevel object segmentation of an image in less than 500ms, with...
David Aldavert, Arnau Ramisa, Ricardo Toledo, Ramo...