Zebra mussels' behaviour detection, extraction and classification using wavelets and kernel methods

Authors:
Piotr Przymus;Krzysztof Rykaczewski;Ryszard Winiewski
Affiliations:
-;-;-
Venue:
Future Generation Computer Systems
Year:
2014

Citing 6
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Abstract

This paper concerns the detection, feature extraction and classification of behaviours of Dreissena polymorpha. A new algorithm based on wavelets and kernel methods that detects relevant events in the collected data is presented. This algorithm allows us to extract elementary events from the behaviour of a living organism. Moreover, we propose an efficient framework for automatic classification to separate the control and stressful conditions.