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ICAISC
2010
Springer
13 years 8 months ago
Pruning Classification Rules with Reference Vector Selection Methods
Attempts to extract logical rules from data often lead to large sets of classification rules that need to be pruned. Training two classifiers, the C4.5 decision tree and the Non-Ne...
Karol Grudzinski, Marek Grochowski, Wlodzislaw Duc...
CVPR
2009
IEEE
15 years 3 months ago
Learning sign language by watching TV (using weakly aligned subtitles)
The goal of this work is to automatically learn a large number of British Sign Language (BSL) signs from TV broadcasts. We achieve this by using the supervisory information avai...
Patrick Buehler (University of Oxford), Mark Everi...
LREC
2010
237views Education» more  LREC 2010»
13 years 9 months ago
Entity Mention Detection using a Combination of Redundancy-Driven Classifiers
We present an experimental framework for Entity Mention Detection in which two different classifiers are combined to exploit Data Redundancy attained through the annotation of a l...
Silvana Marianela Bernaola Biggio, Manuela Speranz...
DIAL
2004
IEEE
164views Image Analysis» more  DIAL 2004»
13 years 12 months ago
A Dynamic Feature Generation System for Automated Metadata Extraction in Preservation of Digital Materials
Obsolescence in storage media and the hardware and software for access and use can render old electronic files inaccessible and unusable. Therefore, the long-term preservation of ...
Song Mao, Jongwoo Kim, George R. Thoma
FLAIRS
2008
13 years 10 months ago
Using Genetic Programming to Increase Rule Quality
Rule extraction is a technique aimed at transforming highly accurate opaque models like neural networks into comprehensible models without losing accuracy. G-REX is a rule extract...
Rikard König, Ulf Johansson, Lars Niklasson