Searched for: subject%3A%22MFCC%22
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Kim, Jaehun (author), Urbano, Julián (author), Liem, C.C.S. (author), Hanjalic, A. (author)
Deep neural networks have frequently been used to directly learn representations useful for a given task from raw input data. In terms of overall performance metrics, machine learning solutions employing deep representations frequently have been reported to greatly outperform those using hand-crafted feature representations. At the same time,...
journal article 2019
Wijnker, Dirk (author)
We investigate how an Unmanned Air Vehicle (UAV) can detect manned aircraft with a single microphone. In particular, we create an audio data set in which UAV ego-sound and recorded aircraft sound can be mixed together, and apply convolutional neural networks to the task of air traffic detection. Due to restrictions on flying UAVs close to...
master thesis 2018
Warmerdam, Santor (author)
Automated instrument recognition is necessary to efficiently obtain instrumentation information for the existing large collections of digital music. While automated instrument recognition is possible with very high accuracy for monophonic fragments, the problem has not yet been solved for polyphonic mixes.In this work a system is designed for...
master thesis 2017