An Adaptive Quality Assessment System-Aspect of Human Factor and Measurement Uncertainty

Document type: Conference Papers
Peer reviewed: Yes
Author(s): Jenny Wirandi, Jiandan Chen, Wlodek Kulesza
Title: An Adaptive Quality Assessment System-Aspect of Human Factor and Measurement Uncertainty
Journal: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Conference name: IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement, Sardagna, ITALY, 2007
Year: 2009
Volume: 58
Issue: 1
Pagination: 68-75
ISSN: 0018-9456
Publisher: IEEE
URI/DOI: 10.1109/TIM.2008.2004981
ISI number: 000261848300010
Organization: Blekinge Institute of Technology
Department: School of Engineering - Dept. of Signal Processing (Sektionen för teknik – avd. för signalbehandling)
School of Engineering S- 372 25 Ronneby
+46 455 38 50 00
http://www.tek.bth.se/
Language: English
Abstract: 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.
Subject: Signal Processing\General
Keywords: Fuzzily defined quantity, image quality, neural network (NN), pulp quality, quality assessment, quality index (QI)
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