A deep learning-based pipeline for mosquito detection and classification from wingbeat sounds
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-13367-0.pdf
Reference35 articles.
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2. Alar HS, Fernandez PL (2021) Classifying mosquito presence and genera using median and interquartile values from 26-filter wingbeat acoustic properties. Procedia Computer Science 193:453–463. https://doi.org/10.1016/j.procs.2021.10.047
3. Arthur BJ, Emr KS, Wyttenbach RA, Hoy RR (2014) Mosquito (Aedes aegypti) flight tones: frequency, harmonicity, spherical spreading, and phase relationships. J Acoust Soc Am 135(2):933–941. https://doi.org/10.1121/1.4861233
4. Chen Y, Why A, Batista G, Mafra-Neto A, Keogh E (2014) Flying insect classification with inexpensive sensors. J Insect Behav 27(5):657–677. https://doi.org/10.1007/s10905-014-9454-4
5. Dombois F, Eckel G (2011) Audification. In: Hermann T, Hunt A, Neuhoff JG (eds) The sonification handbook, pp 301–324. COST and Logos, Chap. 12. https://sonification.de/handbook/
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