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    » Boruta - A System for Feature Selection
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    ICCV
    2003
    IEEE
    309views Computer Vision» more  ICCV 2003»
    On-Line Selection of Discriminative Tracking Features
    15 years 11 months ago
    On-Line Selection of Discriminative Tracking Features
    Download  www.cse.psu.edu
    This paper presents a method for evaluating multiple feature spaces while tracking, and for adjusting the set of features used to improve tracking performance. Our hypothesis is t...
    Robert T. Collins, Yanxi Liu
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    77
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    IROS
    2007
    IEEE
    134views Robotics» more  IROS 2007»
    Feature selection for grasp recognition from optical markers
    15 years 3 months ago
    Feature selection for grasp recognition from optical markers
    Download  www.cs.cmu.edu
    Abstract— Although the human hand is a complex biomechanical system, only a small set of features may be necessary for observation learning of functional grasp classes. We explor...
    Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchel...
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    ESANN
    2004
    112views Neural Networks» more  ESANN 2004»
    A Modular Framework for Multi category feature selection in Digital mammography
    14 years 11 months ago
    A Modular Framework for Multi category feature selection in Digital mammography
    Download  www.dice.ucl.ac.be
    Many existing researches utilized many different approaches for recognition in digital mammography using various ANN classifier-modeling techniques. Different types of feature extr...
    Ranadhir Ghosh, Moumita Ghosh, John Yearwood
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    TIFS
    2008
    113views more  TIFS 2008»
    A Selective Feature Information Approach for Iris Image-Quality Measure
    14 years 9 months ago
    A Selective Feature Information Approach for Iris Image-Quality Measure
    Download  www.engr.iupui.edu
    Poor quality images can significantly affect the accuracy of iris-recognition systems because they do not have enough feature information. However, existing quality measures have f...
    Craig Belcher, Yingzi Du
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    93
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    COLING
    2000
    152views Computational Linguistics» more  COLING 2000»
    Structural Feature Selection For English-Korean Statistical Machine Translation
    14 years 11 months ago
    Structural Feature Selection For English-Korean Statistical Machine Translation
    Download  acl.ldc.upenn.edu
    When aligning texts in very different languages such as Korean and English, structural features beyond word or phrase give useful intbrmation. In this paper, we present a method f...
    Seonho Kim, Juntae Yoon, Mansuk Song
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