Bird Sound Classification Using GLCM Features and LightGBM Applied to Farm Monitoring-Reference-Cited by-同舟云学术

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Bird Sound Classification Using GLCM Features and LightGBM Applied to Farm Monitoring

Published:2023-06-16 Issue: Volume: Page:
ISSN:
Container-title:2023 11th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)
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Author:

Kazeneza Micheline¹,Amenyedzi Destiny Kwabla²,Vodacek Anthony³,Hanyurwimfura Damien²,Ndashimye Emmanuel⁴

Affiliation:

1. University of Rwanda,African Center of Excellence in Internet of Things,Kigali,Rwanda

2. University of Rwanda,African Centre of Excellence in Internet of Things,Kigali,Rwanda

3. Rochester Institute of Technology,Chester F. Carlson Center for Imaging Science,Rochester,New York,USA

4. Carnegie Mellon University Africa,School of ECE,Kigali,Rwanda

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199112/10199257/10200229.pdf?arnumber=10200229

Reference20 articles.

1. A novel feature extraction method for engine sound classification;liu;Applied Acoustics,2019

2. A combination of MFCCs, spectral contrast, and spectral flux to classify bird sounds;gürbüz;27th Signal Processing and Communications Applications Conference (SIU),2019

3. Greedy function approximation: A gradient boosting machine.

4. Textural Features for Image Classification

5. AudioMoth: A low-cost acoustic device for monitoring biodiversity and the environment

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