Abstract
This paper presents the development of a fairly new neural network based method that aims at characterizing polar fleece fabric appearance for the purpose of objective quality evaluation. Co-occurrence matrix analysis is used to give the quantitative descriptions of fabric appearance properties; neural network model is used to establish the relationship between these essential features and the final rating grade of fabric appearance. The experimental results demonstrate that good correlation can be achieved between the actual rating grade and the predicted rating grade and reveals the possibility of the development of artificial intelligence system to simulate the functions of human eyes and brain.
Original language | English |
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Title of host publication | Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010 |
Pages | 417-421 |
Number of pages | 5 |
Volume | 1 |
DOIs | |
Publication status | Published - 16 Nov 2010 |
Event | 2010 6th International Conference on Natural Computation, ICNC'10 - Yantai, Shandong, China Duration: 10 Aug 2010 → 12 Aug 2010 |
Conference
Conference | 2010 6th International Conference on Natural Computation, ICNC'10 |
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Country | China |
City | Yantai, Shandong |
Period | 10/08/10 → 12/08/10 |
Keywords
- Appearance
- Co-occurrence matrix
- Neural network
- Polar fleece fabric
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Biomedical Engineering