Original paper
Evaluation of acoustic pattern recognition of nightingale (Luscinia megarhynchos) recordings by citizens
Abstract
Acoustic pattern recognition methods introduce new perspectives for species identification, biodiversity monitoring and data validation in citizen science but are rarely evaluated in real world scenarios. In this case study we analysed the performance of a machine learning algorithm for automated bird identification to reliably identify common nightingales ( Luscinia megarhynchos ) in field recordings taken by users of the smartphone app...
Paper Details
Title
Evaluation of acoustic pattern recognition of nightingale (Luscinia megarhynchos) recordings by citizens
Published Date
Feb 24, 2020
Journal
Volume
6
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History