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首页> 外文期刊>Neurocomputing >ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm-ISABoost based application in scene categorization
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ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm-ISABoost based application in scene categorization

机译：ISABoost：基于弱分类器内部结构调整的AdaBoost算法-基于ISABoost的场景分类应用

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摘要

AdaBoost algorithms fuse weak classifiers to be a strong classifier by adaptively determine fusion weights of weak classifiers. In this paper, an enhanced AdaBoost algorithm by adjusting inner structure of weak classifiers (ISABoost) is proposed. In the traditional AdaBoost algorithms, the weak classifiers are not changed once they are trained. In ISABoost, the inner structures of weak classifiers are adjusted before their fusion weights determination. ISABoost inherits the advantages of the AdaBoost algorithms in fusing weak classifiers to be a strong classifier. ISABoost gives each weak classifier a second chance to be adjusted stronger. The adjusted weak classifiers are more contributive to make correct classifications for the hardest samples. To show the effectiveness of the proposed ISABoost algorithm, its applications in scene categorization are evaluated. Comparisons of ISABoost and AdaBoost algorithms on three widely utilized scene datasets show the effectiveness of ISABoost algorithm.
机译：AdaBoost算法通过自适应确定弱分类器的融合权重，将弱分类器融合为强分类器。本文提出了一种通过调整弱分类器的内部结构（ISABoost）的增强型AdaBoost算法。在传统的AdaBoost算法中，弱分类器一旦训练就不会改变。在ISABoost中，弱分类器的内部结构会在确定融合权重之前进行调整。 ISABoost继承了AdaBoost算法的优势，可以将弱分类器融合为强分类器。 ISABoost给每个弱分类器第二次被调整为更强的机会。调整后的弱分类器有助于对最困难的样本进行正确的分类。为了展示所提出的ISABoost算法的有效性，评估了其在场景分类中的应用。在三个广泛使用的场景数据集上对ISABoost和AdaBoost算法的比较显示了ISABoost算法的有效性。

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  • 来源
    《Neurocomputing》 |2013年第1期|104-113|共10页
  • 作者

    Xueming Qian; Yuan Yan Tang; Zhe Yan; Kaiyu Hang;

  • 作者单位

    School of Electronic and Information Engineering, Xi'an Jiaotong University, Xianning Road, Xi'an, China,Faculty of Science and Technology, The University of Macau, Macau, China;

    Faculty of Science and Technology, The University of Macau, Macau, China;

    School of Electronic and Information Engineering, Xi'an Jiaotong University, Xianning Road, Xi'an, China;

    School of Electronic and Information Engineering, Xi'an Jiaotong University, Xianning Road, Xi'an, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    AdaBoost; scene categorization; pattern classification; back-propagation networks; SVM; weight learning;

    机译：AdaBoost;场景分类;模式分类反向传播网络;支持向量机;体重学习;

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