DocumentCode
530317
Title
Notice of Retraction
Research on fitness function for surface defect feature selection of steel plate
Author
Gufang Wu ; Haitao Zhang ; Qinghua Zhang ; Yi Pu
Author_Institution
Dept. of Autom., Henan Univ. of Sci. & Technol., Luoyang, China
Volume
1
fYear
2010
fDate
17-19 Sept. 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As variety of surface defect types of steel plates, it is very impendent to find a feature set from original feature set extracted from surface defects, which can express essence characters of defects more effectively and improve defect recognition rate. To settle the problem, genetic algorithm especially fitness function was researched here for the application to defect feature selection on the basis of fully research of theory of information entropy, and average net classification information was used as a fitness function of genetic algorithm to make up for the shortage of using mutual information entropy as fitness function of genetic algorithm. Experiments showed that using optimized feature by genetic algorithm to classify surface defects of steel plates, a higher accurate recognition rate can be achieved.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
As variety of surface defect types of steel plates, it is very impendent to find a feature set from original feature set extracted from surface defects, which can express essence characters of defects more effectively and improve defect recognition rate. To settle the problem, genetic algorithm especially fitness function was researched here for the application to defect feature selection on the basis of fully research of theory of information entropy, and average net classification information was used as a fitness function of genetic algorithm to make up for the shortage of using mutual information entropy as fitness function of genetic algorithm. Experiments showed that using optimized feature by genetic algorithm to classify surface defects of steel plates, a higher accurate recognition rate can be achieved.
Keywords
entropy; genetic algorithms; plates (structures); steel; defect recognition rate; feature set extraction; fitness function; genetic algorithm; mutual information entropy; steel plate; surface defect feature selection; Annealing; Feathers; Silicon; feature selection; fitness function; information entropy; steel strips; surface defects;
fLanguage
English
Publisher
ieee
Conference_Titel
Educational and Information Technology (ICEIT), 2010 International Conference on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-8033-3
Type
conf
DOI
10.1109/ICEIT.2010.5607685
Filename
5607685
Link To Document