Paper Info
Title
Personal Peculiarity Classification Of Flat Finishing Tool Motion By Using Self-Organizing Maps For Skill Training
Abstract
The paper proposes a unsupervised classification method for personal peculiarities in flat finishing motion, which are measured by three dimensional stylus attached to an iron file. The method classifies personal peculiarity variations in order to correct bad finishing motions effectively for skill training. In the case of flat finishing motion, the number of classes of personal peculiarities is unknown. A Self-Organizing Maps is used to classify such unknown number of classes of personal peculiarities.Experimental results of the classification with measured data of an expert and two learners show availability of the proposed method.
Year
Venue
Keywords
2015
2015 10TH ASIAN CONTROL CONFERENCE (ASCC)
time series analysis,organizations,iron
Field
DocType
ISSN
Time series,Computer vision,Computer science,Stylus,Self-organizing map,Artificial intelligence,Motion measurement
Conference
2072-5639
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Masaru Teranishi1179.91
shinpei matsumoto200.34
Hidetoshi Takeno385.99