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  • Compressed Sensing Ensemble Classifier for Human Detection

    Author(s)
    Zhang, Baochang
    Liu, Juan
    Gao, Yongsheng
    Liu, Jianzhuang
    Griffith University Author(s)
    Gao, Yongsheng
    Year published
    2013
    Metadata
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    Abstract
    This paper proposes a novel Compressed Sensing Ensemble Classifier (CSEC) for human detection. The proposed CSEC employs the compressed sensing technique to get a more sparse model with a more reasonable selection of base classifiers. The major contributions of this paper are: 1) a novel principled framework for ensemble classifier design based on compressed sensing; 2) a new concept of considering both the simplicity of ensemble classifier and irrelevance of base classifiers towards optimal classifier design; and 3) a quadratic function for CSEC optimization which includes a new optimizable positive semi-definite relevance ...
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    This paper proposes a novel Compressed Sensing Ensemble Classifier (CSEC) for human detection. The proposed CSEC employs the compressed sensing technique to get a more sparse model with a more reasonable selection of base classifiers. The major contributions of this paper are: 1) a novel principled framework for ensemble classifier design based on compressed sensing; 2) a new concept of considering both the simplicity of ensemble classifier and irrelevance of base classifiers towards optimal classifier design; and 3) a quadratic function for CSEC optimization which includes a new optimizable positive semi-definite relevance matrix to simultaneously select appropriate base classifiers with minimized relevance. Experimental results on INRIA and SDL databases show that the performance of CSEC is better than two most popular classifiers SVM and AdaBoost, as well as a most recent method CLML.
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    Book Title
    Intelligence Science and Big Data Engineering: Lecture Notes in Computer Science
    Volume
    8261
    Publisher URI
    http://dx.doi.org/10.1007/978-3-642-42057-3
    DOI
    https://doi.org/10.1007/978-3-642-42057-3_106
    Subject
    Artificial Intelligence and Image Processing not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/59558
    Collection
    • Book chapters

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