An automatic visual inspection method based on statistical approach for defect detection of ship hull surfaces

Jalalian, A., Lu, W. F., Wong, F. S., Ahmed, S. M. and Chew, C. M. 2018, An automatic visual inspection method based on statistical approach for defect detection of ship hull surfaces, in CASE 2018 : 2018 IEEE International Conference on Automation Science and Engineering, IEEE, Piscataway, N. J., pp. 445-450, doi: 10.1109/COASE.2018.8560341.

Attached Files
Name Description MIMEType Size Downloads

Title An automatic visual inspection method based on statistical approach for defect detection of ship hull surfaces
Author(s) Jalalian, A.
Lu, W. F.
Wong, F. S.
Ahmed, S. M.
Chew, C. M.
Conference name Automation Science and Engineering. Conference (14th : 2018 : Singapore)
Conference location Singapore
Conference dates 2018/08/21 - 2018/08/23
Title of proceedings CASE 2018 : 2018 IEEE International Conference on Automation Science and Engineering
Publication date 2018
Start page 445
End page 450
Total pages 6
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) Science & Technology
Technology
Automation & Control Systems
Engineering, Electrical & Electronic
Engineering
ISBN 9781538635933
ISSN 2161-8070
2161-8089
Language eng
DOI 10.1109/COASE.2018.8560341
HERDC Research category E1.1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2018, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30121137

Document type: Conference Paper
Collection: School of Engineering
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 0 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Tue, 30 Apr 2019, 09:57:28 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.