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An Adaptive Quality Assessment System-Aspect of Human Factor and Measurement Uncertainty
Responsible organisation
2009 (English)In: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, IEEE , 2009, Vol. 58, no 1, 68-75 p.Conference paper, (Refereed) Published
Abstract [en]

In this paper, we discuss a model of quality that makes use of the fuzzily defined variable approach to better understand the concept and, thus, enables the further development of this variable. We propose a general method that may estimate a quality index (QI) that handles both qualitative and quantitative issues. The system further uses a neural network since the system learns how to integrate human factors into a quantitative QI. In our case study, we have examined the measurement of image quality and proposed a theoretical model of pulp quality.

Place, publisher, year, edition, pages
IEEE , 2009. Vol. 58, no 1, 68-75 p.
Keyword [en]
Fuzzily defined quantity, image quality, neural network (NN), pulp quality, quality assessment, quality index (QI)
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-8216DOI: 10.1109/TIM.2008.2004981ISI: 000261848300010Local ID: oai:bth.se:forskinfo5C33131B26A6C5A4C12575B00020B85EOAI: oai:DiVA.org:bth-8216DiVA: diva2:835905
Conference
IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement, Sardagna, ITALY, 2007
Available from: 2012-09-18 Created: 2009-05-08 Last updated: 2015-06-30Bibliographically approved

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Citation style
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