Towards an Automated Acoustic Detection Algorithm for Wood-Boring Beetle Larvae (Coleoptera: Cerambycidae and Buprestidae)
Author:
Affiliation:
1. Stevens Institute of Technology, Hoboken, NJ
2. USDA APHIS PPQ S&T, Buzzards Bay, MA
Publisher
Oxford University Press (OUP)
Subject
Insect Science,Ecology,General Medicine
Link
http://academic.oup.com/jee/article-pdf/112/3/1327/28690050/toz016.pdf
Reference23 articles.
1. Detection-threshold approximation for non-Gaussian backgrounds;Abraham;J. Ocean. Eng,2010
2. Detection of wood boring insects’ larvae based on the acoustic signal analysis and the artificial intelligence algorithm;Bilski;Arch. Acoust,2017
3. Creemers J . 2016. Use of acoustic emission (AE) to detect activity of common European dry-woodboring insects: practical considerations. International Symposium on Non-Destructive Testing in Civil Engineering (NDT-CE). 15–17 September 2015, Berlin, Germany.
4. Automated bioacoustic detection and identification of wood-boring insects for quarantine screening and insect ecology;Farr,2007
5. Hilbert Transform Applications in Mechanical Vibration
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