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Automatic Detection of Cow’s Oestrus in Audio Surveillance System
Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced f...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST)
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4093488/ https://www.ncbi.nlm.nih.gov/pubmed/25049882 http://dx.doi.org/10.5713/ajas.2012.12628 |
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author | Chung, Y. Lee, J. Oh, S. Park, D. Chang, H. H. Kim, S. |
author_facet | Chung, Y. Lee, J. Oh, S. Park, D. Chang, H. H. Kim, S. |
author_sort | Chung, Y. |
collection | PubMed |
description | Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced for the detection of oestrus, a more accurate and practical method is still required. In this paper, we propose an efficient data mining solution for the detection of oestrus, using the sound data of Korean native cows (Bos taurus coreanea). In this method, we extracted the mel frequency cepstrum coefficients from sound data with a feature dimension reduction, and use the support vector data description as an early anomaly detector. Our experimental results show that this method can be used to detect oestrus both economically (even a cheap microphone) and accurately (over 94% accuracy), either as a standalone solution or to complement known methods. |
format | Online Article Text |
id | pubmed-4093488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST) |
record_format | MEDLINE/PubMed |
spelling | pubmed-40934882014-07-21 Automatic Detection of Cow’s Oestrus in Audio Surveillance System Chung, Y. Lee, J. Oh, S. Park, D. Chang, H. H. Kim, S. Asian-Australas J Anim Sci Article Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced for the detection of oestrus, a more accurate and practical method is still required. In this paper, we propose an efficient data mining solution for the detection of oestrus, using the sound data of Korean native cows (Bos taurus coreanea). In this method, we extracted the mel frequency cepstrum coefficients from sound data with a feature dimension reduction, and use the support vector data description as an early anomaly detector. Our experimental results show that this method can be used to detect oestrus both economically (even a cheap microphone) and accurately (over 94% accuracy), either as a standalone solution or to complement known methods. Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST) 2013-07 /pmc/articles/PMC4093488/ /pubmed/25049882 http://dx.doi.org/10.5713/ajas.2012.12628 Text en Copyright © 2013 by Asian-Australasian Journal of Animal Sciences This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License http://creativecommons.org/licenses/by-nc/3.0/ which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Chung, Y. Lee, J. Oh, S. Park, D. Chang, H. H. Kim, S. Automatic Detection of Cow’s Oestrus in Audio Surveillance System |
title | Automatic Detection of Cow’s Oestrus in Audio Surveillance System |
title_full | Automatic Detection of Cow’s Oestrus in Audio Surveillance System |
title_fullStr | Automatic Detection of Cow’s Oestrus in Audio Surveillance System |
title_full_unstemmed | Automatic Detection of Cow’s Oestrus in Audio Surveillance System |
title_short | Automatic Detection of Cow’s Oestrus in Audio Surveillance System |
title_sort | automatic detection of cow’s oestrus in audio surveillance system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4093488/ https://www.ncbi.nlm.nih.gov/pubmed/25049882 http://dx.doi.org/10.5713/ajas.2012.12628 |
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