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master's thesis
Otkrivanje glazbenih žanrova zasnovano na dubokom učenju
2019. urn:nbn:hr:168:241762
Orešković, Krešo
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Orešković, K. (2019). Otkrivanje glazbenih žanrova zasnovano na dubokom učenju (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:241762

Orešković, Krešo. "Otkrivanje glazbenih žanrova zasnovano na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:241762

Orešković, Krešo. "Otkrivanje glazbenih žanrova zasnovano na dubokom učenju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:241762

Orešković, K. (2019). 'Otkrivanje glazbenih žanrova zasnovano na dubokom učenju', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:241762

Orešković K. Otkrivanje glazbenih žanrova zasnovano na dubokom učenju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 April 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:241762

K. Orešković, "Otkrivanje glazbenih žanrova zasnovano na dubokom učenju", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:241762

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Metadata
TitleOtkrivanje glazbenih žanrova zasnovano na dubokom učenju
Title (english)Detection of Musical Genres Using Deep Learning
AuthorKrešo Orešković
MentorMarin Šilić (mentor)
Committee memberMarin Šilić (predsjednik povjerenstva)
Committee memberDejan Škvorc (član povjerenstva)
Committee memberGoran Delač (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-09-23, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Proučiti i opisati duboko učenje kao i popularne programske okvire za duboko učenje. Opisati strategije otkrivanja značajki iz glazbe primjenom značajki dubokog učenja. Programski ostvariti sustav koji određuje žanr iz glazbe u audio formatu pomoću dubokog učenja. Prikazati učinkovitosti ostvarenog sustava korištenjem prikladno odabranih mjera za vrednovanje uspješnosti te opisati dobivene rezultate.
Abstract (english)
To study and describe deep learning as popular programming frameworks for deep learning. To describe strategies of discovery of features from music using features of deep learning. To create a program system that determine the music style in audio format using deep learning. To demonstrate the effectiveness of the system achieved by suitably selected performance evaluation mesaures and to describe the obtained results.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:241762
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2020-01-07 20:50:49