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Multiple Classifier Systems for the Recognition of Orthoptera Songs

机译:多分类器系统的直翅目歌曲识别

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The classification of bioacoustic time series is topic of this paper. In particular, we discuss the combination of local classifier decisions from several feature spaces with static and adaptable fusion schemes, e.g. averaging, voting and decision templates. We present static fusion schemes and algorithms to calculate decision templates, and demonstrate the behaviour of both approaches to bioacoustic applications, the classification of insect songs. Results of these algorithms are presented for species of crickets and katydids. Both families are members of the insect order Orthoptera.
机译:生物声学时间序列的分类是本文的主题。特别是,我们讨论了来自多个特征空间的局部分类器决策与静态和自适应融合方案的结合,例如平均,投票和决策模板。我们提出了静态融合方案和算法来计算决策模板,并演示了两种方法在生物声学应用,昆虫歌曲分类中的行为。给出了algorithms和presented类物种的这些算法的结果。两个家庭都是直翅目昆虫的成员。

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