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CVPR
2009
IEEE
15 years 11 days ago
Learning Mixed Templates for Object Recognition
This article proposes a method for learning object templates composed of local sketches and local textures, and investigates the relative importance of the sketches and textures ...
Haifeng Gong, Song Chun Zhu, Ying Nian Wu, Zhangzh...
BMCBI
2002
195views more  BMCBI 2002»
13 years 6 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
AUSDM
2006
Springer
122views Data Mining» more  AUSDM 2006»
13 years 10 months ago
Analysis of Breast Feeding Data Using Data Mining Methods
The purpose of this study is to demonstrate the benefit of using common data mining techniques on survey data where statistical analysis is routinely applied. The statistical surv...
Hongxing He, Huidong Jin, Jie Chen, Damien McAulla...
BMCBI
2005
155views more  BMCBI 2005»
13 years 6 months ago
Mining protein function from text using term-based support vector machines
Background: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We...
Simon B. Rice, Goran Nenadic, Benjamin J. Stapley
ECCV
2000
Springer
14 years 8 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona