Underwater audio event detection, identification and classification framework (AQUA)

dc.contributor.authorCipli, Gorkem
dc.contributor.supervisorDriessen, Peter F.
dc.date.accessioned2016-12-22T23:12:34Z
dc.date.available2016-12-22T23:12:34Z
dc.date.copyright2016en_US
dc.date.issued2016-12-22
dc.degree.departmentDepartment of Electrical and Computer Engineeringen_US
dc.degree.levelDoctor of Philosophy Ph.D.en_US
dc.description.abstractAn audio event detection and classification framework (AQUA) is developed for the North Pacific underwater acoustic research community. AQUA has been developed, tested, and verified on Ocean Networks Canada (ONC) hydrophone data. Ocean Networks Canada is an non-governmental organization collecting underwater passive acoustic data. AQUA enables the processing of a large acoustic database that grows at a rate of 5 GB per day. Novel algorithms to overcome challenges such as activity detection in broadband non-Gaussian type noise have achieved accurate and high classification rates. The main AQUA modules are blind activity detector, denoiser and classifier. The AQUA algorithms yield promising classification results with accurate time stamps.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/7690
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/ca/*
dc.subjectUnderwater Audio Event Detectionen_US
dc.subjectwhale classificationen_US
dc.subjectOcean Networks Canadaen_US
dc.subjectUnderwater denoiseren_US
dc.titleUnderwater audio event detection, identification and classification framework (AQUA)en_US
dc.typeThesisen_US

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