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» On learning algorithm selection for classification
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128
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ECCV
2006
Springer
16 years 4 months ago
Learning to Detect Objects of Many Classes Using Binary Classifiers
Viola and Jones [VJ] demonstrate that cascade classification methods can successfully detect objects belonging to a single class, such as faces. Detecting and identifying objects t...
Ramana Isukapalli, Ahmed M. Elgammal, Russell Grei...
ICS
2005
Tsinghua U.
15 years 8 months ago
What is worth learning from parallel workloads?: a user and session based analysis
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Julia Zilber, Ofer Amit, David Talby
116
Voted
BMCBI
2006
216views more  BMCBI 2006»
15 years 2 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
WWW
2008
ACM
16 years 3 months ago
Learning deterministic regular expressions for the inference of schemas from XML data
Inferring an appropriate DTD or XML Schema Definition (XSD) for a given collection of XML documents essentially reduces to learning deterministic regular expressions from sets of ...
Geert Jan Bex, Wouter Gelade, Frank Neven, Stijn V...
ICPR
2008
IEEE
16 years 3 months ago
Texture segmentation benchmark
The Prague texture segmentation data-generator and benchmark is a web based (http://mosaic.utia.cas.cz) service designed to mutually compare and rank different texture segmenters,...
Michal Haindl, Stanislav Mikes