Ghosh, Siddhartha and Freitas, Alex and Marshall, Ian (2007) Robust Autonomous Detection of the Faulty Sensors of a Sensor Array. In: 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. IEEE, pp. 233-236. ISBN 978-1-4244-1713-1. (doi:10.1109/CAMSAP.2007.4498008) (KAR id:14523)
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Official URL: http://dx.doi.org/10.1109/CAMSAP.2007.4498008 |
Abstract
We propose a technique for the autonomous detection of the faulty sensors of a sensor array that are aberrant relative to the rest. Our approach is based on probabilistically modeling the distribution of the differences between the sensor measurements as a mixture of gaussians and then classifying further instances of the sensor differences using a naive bayes classifier. We demonstrate the applicability of this technique to the diagnosis of the sensors/photosites of a CCD array, using sensor array data comprising of randomly selected images. Our technique performs well for different combinations of parameter settings at the detection of the faulty photosites of a CCD array.
Item Type: | Book section |
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DOI/Identification number: | 10.1109/CAMSAP.2007.4498008 |
Uncontrolled keywords: | sensor arrays; robustness; fault detection; charge coupled devices; fault diagnosis; Gaussian distribution; charge coupled image sensors; informatics; wheels; digital cameras |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Funders: | Institute of Electrical and Electronics Engineers (https://ror.org/01n002310) |
Depositing User: | Mark Wheadon |
Date Deposited: | 24 Nov 2008 18:04 UTC |
Last Modified: | 12 Jul 2022 10:39 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/14523 (The current URI for this page, for reference purposes) |
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