Automated bioacoustic identification of species

Author:

Chesmore David1

Affiliation:

1. University of York, England

Abstract

Research into the automated identification of animals by bioacoustics is becoming more widespread mainly due to difficulties in carrying out manual surveys. This paper describes automated recognition of insects (Orthoptera) using time domain signal coding and artificial neural networks. Results of field recordings made in the UK in 2002 are presented which show that it is possible to accurately recognize 4 British Orthoptera species in natural conditions under high levels of interference. Work is under way to increase the number of species recognized.

Publisher

FapUNIFESP (SciELO)

Subject

Multidisciplinary

Reference19 articles.

1. Template-based automatic recognition of birdsong syllables from continuous recordings;ANDERSON SE;J Acoust Soc Amer 100,1996

2. Technology Transfer: Applications of Electronic Technology in Ecology and Entomology for Species Identification;CHESMORE ED;Nat Hist Res,1999

3. Application of time domain signal coding and artificial neural networks to passive acoustical identification of animals;CHESMORE ED;Applied Acoustics,2001

Cited by 45 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3