Improving Generalization of Deep Convolutional Neural Networks for Acoustic Scene Classification – Fabian PAISCHER
Fabian PAISCHER
Bachelor's thesis
Improving Generalization of Deep Convolutional Neural Networks for Acoustic Scene Classification
Abstract:
In recent years deep learning has become one of the most popular machine learning techniques for a vast variety of complex problems. An example for such a task is to mirror the human auditory system to classify audio recordings according to the location they were recorded in. This work focuses mainly on the Acoustic Scene Classification task proposed by the IEEE DCASE Challenge. The dataset for Acoustic …moreAbstract:
In recent years deep learning has become one of the most popular machine learning techniques for a vast variety of complex problems. An example for such a task is to mirror the human auditory system to classify audio recordings according to the location they were recorded in. This work focuses mainly on the Acoustic Scene Classification task proposed by the IEEE DCASE Challenge. The dataset for Acoustic …more
Language used: English
Date on which the thesis was submitted / produced: 10. 6. 2018
Thesis defence
- Date of defence: 13. 6. 2018
- Supervisor: prof. Dr. Gerhard Widmer
Citation record
ISO 690-compliant citation record:
PAISCHER, Fabian. \textit{Improving Generalization of Deep Convolutional Neural Networks for Acoustic Scene Classification}. Online. Bachelor's thesis. České Budějovice: University of South Bohemia in České Budějovice, Faculty of Science. 2018. Available from: https://theses.cz/id/9gy6qr/.
The right form of listing the thesis as a source quoted
PAISCHER, Fabian. Improving Generalization of Deep Convolutional Neural Networks for Acoustic Scene Classification. Č. Budějovice, 2018. bakalářská práce (Bc.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta
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Institution archiving the thesis and making it accessible: JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH, Přírodovědecká fakultaUNIVERSITY OF SOUTH BOHEMIA IN ČESKÉ BUDĚJOVICE
Faculty of ScienceBachelor programme / field:
Applied Informatics / Bioinformatics
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