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An Adaptive Quality Assessment System-Aspect of Human Factor and Measurement Uncertainty
Ansvarlig organisasjon
2009 (engelsk)Inngår i: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, IEEE , 2009, Vol. 58, nr 1, s. 68-75Konferansepaper, Publicerat paper (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
IEEE , 2009. Vol. 58, nr 1, s. 68-75
Emneord [en]
Fuzzily defined quantity, image quality, neural network (NN), pulp quality, quality assessment, quality index (QI)
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-8216DOI: 10.1109/TIM.2008.2004981ISI: 000261848300010Lokal ID: oai:bth.se:forskinfo5C33131B26A6C5A4C12575B00020B85EOAI: oai:DiVA.org:bth-8216DiVA, id: diva2:835905
Konferanse
IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement, Sardagna, ITALY, 2007
Tilgjengelig fra: 2012-09-18 Laget: 2009-05-08 Sist oppdatert: 2015-06-30bibliografisk kontrollert

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