Contributions of MIR to soundscape ecology. Part 3: Tagging and classifying audio features using a multi-labeling k-nearest neighbor approach-Reference-Cited by-同舟云学术

Contributions of MIR to soundscape ecology. Part 3: Tagging and classifying audio features using a multi-labeling k-nearest neighbor approach

Published:2019-05 Issue: Volume:51 Page:103-111
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

Bellisario Kristen M.^ORCID,Broadhead Taylor,Savage David^ORCID,Zhao Zhao,Omrani Hichem,Zhang Saihua,Springer John,Pijanowski Bryan C.

Funder

NSF

Sloan Foundation

National Natural Science Foundation

State Scholarship Fund of China

Purdue University

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Ecological Modeling,Modeling and Simulation,Ecology,Ecology, Evolution, Behavior and Systematics

Reference59 articles.

1. Real-time bioacoustics monitoring and automated species identification;Aide;PeerJ,2013

2. Automatic identification of rainfall in acoustic recordings;Bedoya;Ecol. Indic.,2017

3. Contributions of MIR to Soundscape Ecology. Part 1: Potential Methodological Synergies;Bellisario,2019

4. Contributions of MIR to soundscape ecology. Part 2: Spectral timbral analysis for discriminating soundscape components;Bellisario,2019

5. Working with multilabel datasets in R: the mldr package;Charte;R J,2015

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