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 (<i>Balaenoptera musculus</i>) and fin whale (<i>Balaenoptera physalus</i>). A promising method using wavelet scattering transform and deep learning is pro...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/6/3048 |
| _version_ | 1797609065306652672 |
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| author | Farook Sattar |
| author_facet | Farook Sattar |
| author_sort | Farook Sattar |
| collection | DOAJ |
| description | In this paper, we study to improve acoustical methods to identify endangered whale calls with emphasis on the blue whale (<i>Balaenoptera musculus</i>) and fin whale (<i>Balaenoptera physalus</i>). 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. |
| first_indexed | 2024-03-11T05:56:19Z |
| format | Article |
| id | doaj.art-77cc7e454ebe4859ba747b30a0c58cfe |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T05:56:19Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-77cc7e454ebe4859ba747b30a0c58cfe2023-11-17T13:45:13ZengMDPI AGSensors1424-82202023-03-01236304810.3390/s23063048A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin WhaleFarook Sattar0Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 2Y2, CanadaIn this paper, we study to improve acoustical methods to identify endangered whale calls with emphasis on the blue whale (<i>Balaenoptera musculus</i>) and fin whale (<i>Balaenoptera physalus</i>). 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.https://www.mdpi.com/1424-8220/23/6/3048whale callsmarine bioacousticsendangered whaledeep learningartificial intelligencewavelet scattering transform |
| spellingShingle | Farook Sattar A New Acoustical Autonomous Method for Identifying Endangered Whale Calls: A Case Study of Blue Whale and Fin Whale Sensors whale calls marine bioacoustics endangered whale deep learning artificial intelligence wavelet scattering transform |
| title | 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_short | 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 |
| topic | whale calls marine bioacoustics endangered whale deep learning artificial intelligence wavelet scattering transform |
| url | https://www.mdpi.com/1424-8220/23/6/3048 |
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