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| Author(s): |
Diego Furtado Silva
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2014-02-27 |
| Examining board members: |
João Luis Garcia Rosa;
Alexandre Plastino de Carvalho;
Estevam Rafael Hruschka Júnior
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| Advisor: | Gustavo Enrique de Almeida Prado Alves Batista |
| Abstract | |
One of the major challenges in data mining is the integration of temporal data to its process. There are a number of emerging applications that involve temporal data, including fraud detection in credit card transactions and phone calls, intrusion detection in computer systems, the prediction of secondary structures of proteins, the analysis of data from sensors, and many others. In this work, our main interest is the classification of time series that represent audio signals. Our main interest is an application for classifying signals of insects collected from an optical sensor, which should count and classify insects automatically. Although these signals are optically collected, they resemble audio signals. The objective of this research is to compare classification methods based on similarity and feature extraction in the context of insects classification. For this purpose, we used the main classification methods for audio signals, which have been proposed for problems such as musical instrument, speech and animal species recognition. This work shows that, in general, the approach based on feature extraction is more accurate than the classification by similarity. More specifically, the best results are obtained with mel-frequency cepstrum coefficients. This work also presents significant contributions in other applications, also related to the analysis of time series and audio signals by similarity and feature extraction (AU) | |
| FAPESP's process: | 11/04054-2 - Time series classification by similarity and extraction of intrinsic attributes with application to insect species identification |
| Grantee: | Diego Furtado Silva |
| Support Opportunities: | Scholarships in Brazil - Master |