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    » Co-Tracking Using Semi-Supervised Support Vector Machines
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    BMCBI
    2005
    122views more  BMCBI 2005»
    Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine
    13 years 7 months ago
    Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine
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    Chenghai Xue, Fei Li, Tao He, Guo-Ping Liu, Yanda ...
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    BMCBI
    2005
    136views more  BMCBI 2005»
    Gene/protein name recognition based on support vector machine using dictionary as features
    13 years 7 months ago
    Gene/protein name recognition based on support vector machine using dictionary as features
    Download  www.biomedcentral.com
    Background: Automated information extraction from biomedical literature is important because a vast amount of biomedical literature has been published. Recognition of the biomedic...
    Tomohiro Mitsumori, Sevrani Fation, Masaki Murata,...
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    ESWA
    2010
    132views more  ESWA 2010»
    Prediction of small non-coding RNA in bacterial genomes using support vector machines
    13 years 2 months ago
    Prediction of small non-coding RNA in bacterial genomes using support vector machines
    Download  ir.lib.nctu.edu.tw
    Tzu-Hao Chang, Li-Ching Wu, Jun-Hong Lin, Hsien-Da...
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    TR
    2010
    204views Hardware» more  TR 2010»
    Anomaly Detection Through a Bayesian Support Vector Machine
    13 years 2 months ago
    Anomaly Detection Through a Bayesian Support Vector Machine
    Download  www6.cityu.edu.hk
    This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
    Vasilis A. Sotiris, Peter W. Tse, Michael Pecht
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    TIP
    2008
    128views more  TIP 2008»
    Wavelet Frame Accelerated Reduced Support Vector Machines
    13 years 7 months ago
    Wavelet Frame Accelerated Reduced Support Vector Machines
    Download  gravis.cs.unibas.ch
    In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
    Matthias Rätsch, Gerd Teschke, Sami Romdhani,...
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