Automatic bird sound detection: logistic regression based acoustic occupancy model-Reference-Cited by-同舟云学术

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Automatic bird sound detection: logistic regression based acoustic occupancy model

Published:2020-02-24 Issue:3 Volume:30 Page:324-340
ISSN:0952-4622
Container-title:Bioacoustics
language:en
Short-container-title:Bioacoustics

Author:

Tseng Yi-Chin¹^ORCID,Eskelson Bianca N. I.¹,Martin Kathy²³,LeMay Valerie¹

Affiliation:

1. Department of Forest Resources Management, University of British Columbia, Vancouver, Canada

2. Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, Canada

3. Environment and Climate Change Canada, Pacific Wildlife Research Centre, Vancouver, BC, Canada

Funder

Soundscape Association of Taiwan

Publisher

Informa UK Limited

Subject

Ecology,Ecology, Evolution, Behavior and Systematics

Link

https://www.tandfonline.com/doi/pdf/10.1080/09524622.2020.1730241

Reference56 articles.

1. Stacked convolutional and recurrent neural networks for bird audio detection

2. Allaire JJ, Chollet F. 2019. keras: R interface to ‘Keras’. [online]; [Accessed 2020 Jan 24]. https://CRAN.R-project.org/package=keras

3. THE SCALING OF SONG FREQUENCY IN CICADAS

4. Suppression of acoustic noise in speech using spectral subtraction

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1. Automatic Bird Sound Source Separation Based on Passive Acoustic Devices in Wild Environment;IEEE Internet of Things Journal;2024-05-01

2. Bird Call Recognition using Acoustic based Feature Selection approach in Machine Learning;2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA);2023-08-18

3. Western Mediterranean Wetland Birds dataset: A new annotated dataset for acoustic bird species classification;Ecological Informatics;2023-07

4. Multiple Musical Instrument Signal Recognition Based on Convolutional Neural Network;Scientific Programming;2022-03-25

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