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Article

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Accepted version

Publication date

2005

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/125468

Fuzzy k-NN applied to mould detection

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Related resource

https://doi.org/10.1016/j.snb.2004.05.066

Abstract

The possibility to detect Aspergillus versicolor growing on different building materials by a metal oxide sensor array is studied. Results show that an accurate classification rate of 89 ± 3% can be obtained combining an extended linear discriminant analysis plus a fuzzy k-NN classifier. The classification ability of the classifier is assessed within the dataset by crossvalidation and also in a second dataset collected 5 months later. There is a slight decrease in the classification performance for all the algorithms, being the most sensitive the most accurate one.

Subject

Conjunts borrosos, Xarxes de sensors

Subject (English)

Fuzzy sets, Sensor networks

Citation

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Articles publicats en revistes (Enginyeria Electrònica i Biomèdica)

Citation

KUSKE, M., et al. Fuzzy k-NN applied to mould detection. Sensors and Actuators B-Chemical. 2005. Vol. 106, num. 52-60. ISSN 0925-4005. [consulted: 10 of August of 2026]. Available at: https://hdl.handle.net/2445/125468

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