Information: Join today and make your research activities more affordable! Technical workshop participation fees and annual registration fees are available at member rates.
Notice: [Important] Announcement of Changes to Registration Fee Payment and Manuscript Upload Procedures for IEICE Technical Meetings
IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2017-10-13 15:20
Automatic Visual Inspection of Metal Pressed Parts Using CNN
Katsuhisa Kitaguchi, Yohei Nishizaki, Mamoru Saito (ORIST) PRMU2017-95
Abstract (in Japanese) (See Japanese page) 
(in English) We have been developing a deep learning-based method for automated visual inspection of deep drawing metal products. Deep drawing is a process technology that forms a sheet metal beyond its limits of ordinary stamping, which often suffers from surface defects due to lack of material strength, improper lubrication and contamination. It was difficult to detect these kind of defects by conventional two class CNN model,ie normal and defective.
Here, we propose a CNN model for multi-label classification to find various surface defects. In the experiment, we compare our model with the conventional two class model, and show the improvement of classification performance. We also examine the functional difference of the convolution filters between both models.
Keyword (in Japanese) (See Japanese page) 
(in English) CNN / Visual inspection / Metal parts / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 238, PRMU2017-95, pp. 181-186, Oct. 2017.
Paper # PRMU2017-95 
Date of Issue 2017-10-05 (PRMU) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2017-95

Conference Information
Committee PRMU  
Conference Date 2017-10-12 - 2017-10-13 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2017-10-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Visual Inspection of Metal Pressed Parts Using CNN 
Sub Title (in English)  
Keyword(1) CNN  
Keyword(2) Visual inspection  
Keyword(3) Metal parts  
Keyword(4)  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Katsuhisa Kitaguchi  
1st Author's Affiliation Osaka Research Institute of Industrial Science and Technology (ORIST)
2nd Author's Name Yohei Nishizaki  
2nd Author's Affiliation Osaka Research Institute of Industrial Science and Technology (ORIST)
3rd Author's Name Mamoru Saito  
3rd Author's Affiliation Osaka Research Institute of Industrial Science and Technology (ORIST)
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
21st Author's Name  
21st Author's Affiliation ()
22nd Author's Name  
22nd Author's Affiliation ()
23rd Author's Name  
23rd Author's Affiliation ()
24th Author's Name  
24th Author's Affiliation ()
25th Author's Name  
25th Author's Affiliation ()
26th Author's Name / /
26th Author's Affiliation ()
()
27th Author's Name / /
27th Author's Affiliation ()
()
28th Author's Name / /
28th Author's Affiliation ()
()
29th Author's Name / /
29th Author's Affiliation ()
()
30th Author's Name / /
30th Author's Affiliation ()
()
31st Author's Name / /
31st Author's Affiliation ()
()
32nd Author's Name / /
32nd Author's Affiliation ()
()
33rd Author's Name / /
33rd Author's Affiliation ()
()
34th Author's Name / /
34th Author's Affiliation ()
()
35th Author's Name / /
35th Author's Affiliation ()
()
36th Author's Name / /
36th Author's Affiliation ()
()
Speaker Author-1 
Date Time 2017-10-13 15:20:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2017-95 
Volume (vol) vol.117 
Number (no) no.238 
Page pp.181-186 
#Pages 6 
Date of Issue 2017-10-05 (PRMU) 

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan