Automatic Detectors for Underwater Soundscape Measurements
dc.contributor.author | Madhusudhana, Shyam Kumar | |
dc.contributor.supervisor | Dr Christine Erbe | |
dc.contributor.supervisor | Assoc. Prof. Alexander Gavrilov | |
dc.date.accessioned | 2017-01-30T09:52:04Z | |
dc.date.available | 2017-01-30T09:52:04Z | |
dc.date.created | 2016-11-03T05:32:52Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/649 | |
dc.description.abstract |
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. | |
dc.language | en | |
dc.publisher | Curtin University | |
dc.title | Automatic Detectors for Underwater Soundscape Measurements | |
dc.type | Thesis | |
dcterms.educationLevel | PhD | |
curtin.department | Department of Physics and Astronomy, Centre for Marine Science and Technology | |
curtin.accessStatus | Open access |