• The effectiveness of classifier combination and the problem of best combination both have to be solved.

    分类器组合的有效性问题以及最佳组合问题均需要解决。

    youdao

  • To enhance the accuracy of image classification, proposed hybrid multiple classifier combination method from abstract level and measurement level.

    为了提高遥感影像分类精度,从抽象级和测量级的两个层次出发,提出混合多分类器结合算法。

    youdao

  • Aiming at the deficiency of evaluating classifier combination methods with standard data sets, a new classifier simulation algorithm was proposed.

    针对标准数据集在评估多分类器系统的组合方法时存在的不足,设计了一种新的分类器模拟算法。

    youdao

  • The techniques of mis-recognition model and multiple classifier combination are proposed and used in the system.

    在车牌字符识别中引入了误识模型和多分类器集成技术。

    youdao

  • In chapter 3, the method of multi classifier combination based on different pattern features is studied.

    第三章,研究了基于不同模式特征的多分类器联合方法问题。

    youdao

  • The goal of classifier selection is to select a subset of classifiers from a given set of candidate classifiers, to achieve the best combination performance.

    分类器选择是一种设计多分类器系统的有效方法,从给定候选分类器集中挑选出一个子集,使得该子集集成性能最佳。

    youdao

  • A method of speaker recognition based on sub-band processing and multi-classifier combination is presented.

    提出了一种基于子带处理多分类器融合的说话人识别方法。

    youdao

  • Aiming at improving the classification performance, a combination model of multiple classifier systems is presented, which takes the Sum rule and majority voting as its special cases.

    为改进多分类器系统的性能,提出一个多分类器融合模型,该模型将和规则与多数投票作为特例纳入其体系中。

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  • As a common method, Multi-classifier combination falls across challenges no matter that in series or in parallel, or even be mixture of both.

    组合分类方法是行人检测中常用的方法,但是无论是串联还是并联的方法,甚至串联和并联相结合的方法,都在行人检测中遇到了挑战。

    youdao

  • The objective of multi-classifier combination is to make use of each classifier"s good qualities in recognition performance and gains higher recognition rate than each classifier."

    多分类器组合的目的是希望能够充分发挥每个分类器在各自分类性能上的长处,以获得比任何单独分类器都要高的识别率。

    youdao

  • The objective of multi-classifier combination is to make use of each classifier"s good qualities in recognition performance and gains higher recognition rate than each classifier."

    多分类器组合的目的是希望能够充分发挥每个分类器在各自分类性能上的长处,以获得比任何单独分类器都要高的识别率。

    youdao

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