A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale
In this paper, we study to improve acoustical methods to identify endangered whale calls with emphasis on the blue whale ( Balaenoptera musculus ) and fin whale ( Balaenoptera physalus ). A promising method using wavelet scattering transform and deep learning is proposed here to detect/classify the...
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ftdoajarticles:oai:doaj.org/article:77cc7e454ebe4859ba747b30a0c58cfe 2023-06-11T04:10:27+02:00 A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale Farook Sattar 2023-03-01T00:00:00Z https://doi.org/10.3390/s23063048 https://doaj.org/article/77cc7e454ebe4859ba747b30a0c58cfe EN eng MDPI AG https://www.mdpi.com/1424-8220/23/6/3048 https://doaj.org/toc/1424-8220 doi:10.3390/s23063048 1424-8220 https://doaj.org/article/77cc7e454ebe4859ba747b30a0c58cfe Sensors, Vol 23, Iss 3048, p 3048 (2023) whale calls marine bioacoustics endangered whale deep learning artificial intelligence wavelet scattering transform Chemical technology TP1-1185 article 2023 ftdoajarticles https://doi.org/10.3390/s23063048 2023-05-07T00:34:38Z In this paper, we study to improve acoustical methods to identify endangered whale calls with emphasis on the blue whale ( Balaenoptera musculus ) and fin whale ( Balaenoptera physalus ). A promising method using wavelet scattering transform and deep learning is proposed here to detect/classify the whale calls quite precisely in the increasingly noisy ocean with a small dataset. The performances shown in terms of classification accuracy (>97%) demonstrate the efficiency of the proposed method which outperforms the relevant state-of-the-art methods. In this way, passive acoustic technology can be enhanced to monitor endangered whale calls. Efficient tracking of their numbers, migration paths and habitat become vital to whale conservation by lowering the number of preventable injuries and deaths while making progress in their recovery. Article in Journal/Newspaper Balaenoptera musculus Balaenoptera physalus Blue whale Fin whale Directory of Open Access Journals: DOAJ Articles Sensors 23 6 3048 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
whale calls marine bioacoustics endangered whale deep learning artificial intelligence wavelet scattering transform Chemical technology TP1-1185 |
spellingShingle |
whale calls marine bioacoustics endangered whale deep learning artificial intelligence wavelet scattering transform Chemical technology TP1-1185 Farook Sattar A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale |
topic_facet |
whale calls marine bioacoustics endangered whale deep learning artificial intelligence wavelet scattering transform Chemical technology TP1-1185 |
description |
In this paper, we study to improve acoustical methods to identify endangered whale calls with emphasis on the blue whale ( Balaenoptera musculus ) and fin whale ( Balaenoptera physalus ). A promising method using wavelet scattering transform and deep learning is proposed here to detect/classify the whale calls quite precisely in the increasingly noisy ocean with a small dataset. The performances shown in terms of classification accuracy (>97%) demonstrate the efficiency of the proposed method which outperforms the relevant state-of-the-art methods. In this way, passive acoustic technology can be enhanced to monitor endangered whale calls. Efficient tracking of their numbers, migration paths and habitat become vital to whale conservation by lowering the number of preventable injuries and deaths while making progress in their recovery. |
format |
Article in Journal/Newspaper |
author |
Farook Sattar |
author_facet |
Farook Sattar |
author_sort |
Farook Sattar |
title |
A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale |
title_short |
A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale |
title_full |
A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale |
title_fullStr |
A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale |
title_full_unstemmed |
A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale |
title_sort |
new acoustical autonomous method for identifying endangered whale calls: a case study of blue whale and fin whale |
publisher |
MDPI AG |
publishDate |
2023 |
url |
https://doi.org/10.3390/s23063048 https://doaj.org/article/77cc7e454ebe4859ba747b30a0c58cfe |
genre |
Balaenoptera musculus Balaenoptera physalus Blue whale Fin whale |
genre_facet |
Balaenoptera musculus Balaenoptera physalus Blue whale Fin whale |
op_source |
Sensors, Vol 23, Iss 3048, p 3048 (2023) |
op_relation |
https://www.mdpi.com/1424-8220/23/6/3048 https://doaj.org/toc/1424-8220 doi:10.3390/s23063048 1424-8220 https://doaj.org/article/77cc7e454ebe4859ba747b30a0c58cfe |
op_doi |
https://doi.org/10.3390/s23063048 |
container_title |
Sensors |
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23 |
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6 |
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3048 |
_version_ |
1768384850999377920 |