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» On learning algorithm selection for classification
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ECCV
2006
Springer
16 years 2 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 6 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
101
Voted
BMCBI
2006
216views more  BMCBI 2006»
15 years 24 days 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 1 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...
112
Voted
ICPR
2008
IEEE
16 years 1 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