The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Call for Papers
  • Proposals
  • Guest Editors

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

KNN and SVM Classification for Chainsaw Sound Identification in the Forest Areas

Author 1: N’tcho Assoukpou Jean GNAMELE
Author 2: Yelakan Berenger OUATTARA
Author 3: Toka Arsene KOBEA
Author 4: Geneviève BAUDOIN
Author 5: Jean-Marc LAHEURTE

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2019.0101270

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: We present in this paper a comparative study of two classifiers, namely, SVM (support vector machine) and KNN (K-Nearest Neighbors), which we combine to MFCC (Mel-Frequency Cepstral Coefficients) in order to make possible the detection of chainsaw’s sounds in a forest environment. Optimization’s calculation of the relevant characteristics of the sounds recorded in the forest and the judicious choice of the key parameters of the classifiers allows us to obtain a true positive rate of 95.63% for the SVM-LOG-KERNEL and 94.02% for the KNN. The SVM-LOG-KERNEL classifier offers a better classification result and a processing time 30 times faster than KNN.

Keywords: KNN Algorithm; SVM Algorithm; MFCC; sound recognition; forest monitoring; machine learning

N’tcho Assoukpou Jean GNAMELE, Yelakan Berenger OUATTARA, Toka Arsene KOBEA, Geneviève BAUDOIN and Jean-Marc LAHEURTE, “KNN and SVM Classification for Chainsaw Sound Identification in the Forest Areas” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101270

@article{GNAMELE2019,
title = {KNN and SVM Classification for Chainsaw Sound Identification in the Forest Areas},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101270},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101270},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {N’tcho Assoukpou Jean GNAMELE and Yelakan Berenger OUATTARA and Toka Arsene KOBEA and Geneviève BAUDOIN and Jean-Marc LAHEURTE}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2022

3-4 March 2022

  • Virtual

Computing Conference 2022

14-15 July 2022

  • Hybrid / London, UK

IntelliSys 2022

1-2 September 2022

  • Hybrid / Amsterdam

Future Technologies Conference (FTC) 2022

20-21 October 2022

  • Hybrid / Vancouver
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org