Automatic Detectors for Underwater Soundscape Measurements
Environmental impact regulations require that marine industrial operators quantify their contribution to underwater noise scenes. Automation of such assessments becomes feasible with the successful categorisation of sounds into broader classes based on source types – biological, anthropogenic and ph...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
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Curtin University
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/649 |
| _version_ | 1848743439653404672 |
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| author | Madhusudhana, Shyam Kumar |
| author_facet | Madhusudhana, Shyam Kumar |
| author_sort | Madhusudhana, Shyam Kumar |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Environmental impact regulations require that marine industrial operators quantify their contribution to underwater noise scenes. Automation of such assessments becomes feasible with the successful categorisation of sounds into broader classes based on source types – biological, anthropogenic and physical. Previous approaches to passive acoustic monitoring have mostly been limited to a few specific sources of interest. In this study, source-independent signal detectors are developed and a framework is presented for the automatic categorisation of underwater sounds into the aforementioned classes. |
| first_indexed | 2025-11-14T05:45:35Z |
| format | Thesis |
| id | curtin-20.500.11937-649 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:45:35Z |
| publishDate | 2015 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-6492017-02-20T06:41:21Z Automatic Detectors for Underwater Soundscape Measurements Madhusudhana, Shyam Kumar Environmental impact regulations require that marine industrial operators quantify their contribution to underwater noise scenes. Automation of such assessments becomes feasible with the successful categorisation of sounds into broader classes based on source types – biological, anthropogenic and physical. Previous approaches to passive acoustic monitoring have mostly been limited to a few specific sources of interest. In this study, source-independent signal detectors are developed and a framework is presented for the automatic categorisation of underwater sounds into the aforementioned classes. 2015 Thesis http://hdl.handle.net/20.500.11937/649 en Curtin University fulltext |
| spellingShingle | Madhusudhana, Shyam Kumar Automatic Detectors for Underwater Soundscape Measurements |
| title | Automatic Detectors for Underwater Soundscape Measurements |
| title_full | Automatic Detectors for Underwater Soundscape Measurements |
| title_fullStr | Automatic Detectors for Underwater Soundscape Measurements |
| title_full_unstemmed | Automatic Detectors for Underwater Soundscape Measurements |
| title_short | Automatic Detectors for Underwater Soundscape Measurements |
| title_sort | automatic detectors for underwater soundscape measurements |
| url | http://hdl.handle.net/20.500.11937/649 |