Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Automated surface inspection"'
Publikováno v:
IEEE Access, Vol 8, Pp 114088-114099 (2020)
Automated surface inspection (ASI) is critical to quality control in industrial manufacturing processes. Recent advances in deep learning have produced new ASI methods that automatically learn high-level features from training samples while being rob
Externí odkaz:
https://doaj.org/article/96195d69f1ee446696becf28c0a258b2
Akademický článek
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Autor:
Wei-Peng Tang, Sze-Teng Liong, Chih-Cheng Chen, Ming-Han Tsai, Ping-Cheng Hsieh, Yu-Ting Tsai, Shih-Hsin Chen, Kun-Ching Wang
Publikováno v:
Applied Sciences, Vol 11, Iss 20, p 9473 (2021)
With the advancement of industrial intelligence, defect recognition has become an indispensable part of facilitating surface quality in the steel manufacturing process. To assure product quality, most previous studies were typically trained with many
Externí odkaz:
https://doaj.org/article/bb60a4532f3b4781a6d663ae2d4b00ae
Akademický článek
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Publikováno v:
Applied Sciences, Vol 9, Iss 15, p 3159 (2019)
Aiming at the problems of complex texture, variable interference factors and large sample acquisition in surface defect detection, a generic method of automated surface defect detection based on a bilinear model was proposed. To realize the automatic
Externí odkaz:
https://doaj.org/article/f65dfb6e657b4cb9838cdd9ae12d26be
Autor:
Yu-Ting Tsai, Chih-Cheng Chen, Ping-Cheng Hsieh, Shih-Hsin Chen, Wei-Peng Tang, Kun-Ching Wang, Sze-Teng Liong, Ming-Han Tsai
Publikováno v:
Applied Sciences
Volume 11
Issue 20
Applied Sciences, Vol 11, Iss 9473, p 9473 (2021)
Volume 11
Issue 20
Applied Sciences, Vol 11, Iss 9473, p 9473 (2021)
With the advancement of industrial intelligence, defect recognition has become an indispensable part of facilitating surface quality in the steel manufacturing process. To assure product quality, most previous studies were typically trained with many
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7048468ed2e9748db166fef0c2195629
https://doi.org/10.3390/app11209473
https://doi.org/10.3390/app11209473
Akademický článek
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K zobrazení výsledku je třeba se přihlásit.
Akademický článek
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Publikováno v:
Applied Sciences
Volume 9
Issue 15
Applied Sciences, Vol 9, Iss 15, p 3159 (2019)
Volume 9
Issue 15
Applied Sciences, Vol 9, Iss 15, p 3159 (2019)
Aiming at the problems of complex texture, variable interference factors and large sample acquisition in surface defect detection, a generic method of automated surface defect detection based on a bilinear model was proposed. To realize the automatic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f07ba6f0c8183f0f220d54f2d4565064
Publikováno v:
Maestro-Watson, D, Balzategui, J, Eciolaza, L & Arana-Arexolaleiba, N 2019, Deep Learning for Deflectometric Inspection of Specular Surfaces . in J A Saez, E Corchado, A Herrero, M Grana, J M Lopez-Guede, O Etxaniz & H Quintian (eds), International Joint Conference SOCO’18-CISIS’18-ICEUTE’18, Proceedings . Springer, Advances in Intelligent Systems and Computing, vol. 771, pp. 280-289, International Joint Conference: 13th International Conference on Soft Computing Models, SOCO 2018, 11th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2018 and 9th International Conference on EUropean Transnational Education, ICEUTE 2018, san sebastian, Spain, 06/06/2018 . https://doi.org/10.1007/978-3-319-94120-2_27
Deflectometric techniques provide abundant information useful for aesthetic defect inspection in specular and glossy/shinny surfaces. A series of light patterns is observed indirectly through their reflection on the surface under inspection, and diff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::48d60c5476499131e0ca8ab9111db2c1
https://vbn.aau.dk/da/publications/db136a06-a0c4-4998-b1c3-71103cf8e501
https://vbn.aau.dk/da/publications/db136a06-a0c4-4998-b1c3-71103cf8e501
