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作者:

Lu, Shengfu (Lu, Shengfu.) | Li, Peng (Li, Peng.) | Li, Mi (Li, Mi.) (学者:栗觅)

收录:

CPCI-S

摘要:

The method from DS evidence theory based multi-modal information decision fusion uses the classification structure information which the correct and error classification information provided by the classifiers. These two types of information affect the fusion results of DS evidence theory. This paper proposes a new method(DShW) for correct and error classification information in the balanced classification structure information based on DS evidence theory. That is, a method based on inertia weight normalization is introduced in the confusion matrix. To adjust the specific gravity of correct and error classification in classification structure information by changing the size of the value h, so as to achieve the purpose of balancing correct and error classification information. By comparing with other classifiers, we find that the DShW method effectively improves the accuracy of decision fusion.

关键词:

decision-level fusion multimodal data fusion DS evidence theory inertia weight

作者机构:

  • [ 1 ] [Lu, Shengfu]Beijing Univ Technol, Fac Informat Technol, Dept Automat, Beijing, Peoples R China
  • [ 2 ] [Li, Peng]Beijing Univ Technol, Fac Informat Technol, Dept Automat, Beijing, Peoples R China
  • [ 3 ] [Li, Mi]Beijing Univ Technol, Fac Informat Technol, Dept Automat, Beijing, Peoples R China

通讯作者信息:

  • 栗觅

    [Li, Mi]Beijing Univ Technol, Fac Informat Technol, Dept Automat, Beijing, Peoples R China

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来源 :

PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020)

年份: 2020

页码: 1684-1690

语种: 英文

被引次数:

WoS核心集被引频次: 6

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

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中文被引频次:

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