Turning wingbeat sounds into spectrum images for acoustic insect classification
| Autor: | Joni-Kristian Kämäräinen, Gaojuan Fan, Ke Chen, Chongsheng Zhang, Pengyou Wang, Hui Guo |
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| Rok vydání: | 2017 |
| Předmět: |
Signal processing
Artificial neural network Contextual image classification business.industry Computer science 020207 software engineering 02 engineering and technology Convolutional neural network Frequency spectrum 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Electrical and Electronic Engineering business Classifier (UML) Optoacoustic imaging |
| Zdroj: | Electronics Letters. 53:1674-1676 |
| ISSN: | 1350-911X 0013-5194 |
| DOI: | 10.1049/el.2017.3334 |
| Popis: | A novel acoustic insect classifier on deep convolutional feature of frequency spectrum images generated by their wingbeat sounds is introduced. By visualising insect wingbeat sound, the proposed method is the first attempt to convert time-series acoustic signal processing to image recognition, which has recently gained significant improvement with convolutional neural networks. Experiments show the better accuracy of the proposed method on the public UCR flying insect datasets compared with the state-of-the-art methods. |
| Databáze: | OpenAIRE |
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