Abstract
In the current paper we consider the task of object classification in wireless sensor networks. Due to restricted battery capacity, minimizing the energy consumption is a main concern in wireless sensor networks. Assuming that each feature needed for classification is acquired by a sensor, a sequential classifier combination approach is proposed that aims at minimizing the number of features used for classification while maintaining a given correct classification rate. In experiments with data from the UCI repository, the feasibility of this approach is demonstrated.
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Csirik, J., Bertholet, P., Bunke, H. (2011). Sequential Classifier Combination for Pattern Recognition in Wireless Sensor Networks. In: Sansone, C., Kittler, J., Roli, F. (eds) Multiple Classifier Systems. MCS 2011. Lecture Notes in Computer Science, vol 6713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21557-5_21
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DOI: https://doi.org/10.1007/978-3-642-21557-5_21
Publisher Name: Springer, Berlin, Heidelberg
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