人体回声定位
鉴定(生物学)
分类器(UML)
物种鉴定
计算机科学
人工智能
生态学
生物
动物
神经科学
作者
Martin К. Obrist,Ruedi Boesch,Peter F. Flückiger
出处
期刊:Mammalia
[De Gruyter]
日期:2004-12-01
卷期号:68 (4): 307-322
被引量:175
标识
DOI:10.1515/mamm.2004.030
摘要
Pattern recognition algorithms offer a promising approach to recognizing bat species by their echolocation calls. Automated systems like synergetic classifiers may contribute significantly to operator-independent species identification in the field. However, it necessitates the assembling of an appropriate database of reference calls, a task far from trivial. We present data on species specific flexibility in call parameters of all Swiss bat species (except Nyctalus lasiopterus and Plecotus alpinus ). The selection of "training-calls" for the classifier is crucial for species identification success. We discuss this in the context of echolocation call variability differing between species and its consequences for the implementation of an automated, species specific bat activity monitoring system.
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