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» Calibrating Random Forests
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ISCI
2007
130views more  ISCI 2007»
13 years 8 months ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
MICCAI
2009
Springer
14 years 10 months ago
Discriminative, Semantic Segmentation of Brain Tissue in MR Images
A new algorithm is presented for the automatic segmentation and classification of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classification and ta...
Zhao Yi, Antonio Criminisi, Jamie Shotton, Andr...
DAGM
2009
Springer
14 years 3 months ago
Learning with Few Examples by Transferring Feature Relevance
The human ability to learn difficult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
Erik Rodner, Joachim Denzler
JAIR
2008
93views more  JAIR 2008»
13 years 8 months ago
Spectrum of Variable-Random Trees
In this paper, we show that a continuous spectrum of randomisation exists, in which most existing tree randomisations are only operating around the two ends of the spectrum. That ...
Fei Tony Liu, Kai Ming Ting, Yang Yu, Zhi-Hua Zhou
IJSNET
2010
114views more  IJSNET 2010»
13 years 7 months ago
Wireless sensor networks for soil science
Abstract: Wireless sensor networks can revolutionize soil ecology by providing measurements at temporal and spatial granularities previously impossible. This paper presents our fi...
Andreas Terzis, Razvan Musaloiu-Elefteri, Joshua C...