Show simple item record

dc.contributor.authorMadhusudhana, Shyam Kumar
dc.contributor.supervisorDr Christine Erbe
dc.contributor.supervisorAssoc. Prof. Alexander Gavrilov

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.publisherCurtin University
dc.titleAutomatic Detectors for Underwater Soundscape Measurements
curtin.departmentDepartment of Physics and Astronomy, Centre for Marine Science and Technology
curtin.accessStatusOpen access

Files in this item


This item appears in the following Collection(s)

Show simple item record