Açık Akademik Arşiv Sistemi

An industrial visual inspection system that uses inductive learning

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dc.contributor.authors Aksoy, MS; Torkul, O; Cedimoglu, IH;
dc.date.accessioned 2020-01-17T08:43:55Z
dc.date.available 2020-01-17T08:43:55Z
dc.date.issued 2004
dc.identifier.citation Aksoy, MS; Torkul, O; Cedimoglu, IH; (2004). An industrial visual inspection system that uses inductive learning. JOURNAL OF INTELLIGENT MANUFACTURING, 15, 574-569
dc.identifier.issn 0956-5515
dc.identifier.uri https://hdl.handle.net/20.500.12619/6439
dc.description.abstract This paper presents an industrial visual inspection system that uses inductive learning. The system employs RULES-3 inductive learning algorithm to extract the necessary set of rules and template matching technique to process an image. Twenty 3 x 3 masks are used to represent an image. Each example consists of 20 frequencies of each mask. The system was tested on five different types of tea or water cups in order to classify the good and bad items. The system was trained using five good cups and then tested for 113 unseen examples. The results obtained showed the high performance of the system: the efficiency of the system for correctly classifying unseen examples was 100%. The system can also decide what type of the cup is being processed.
dc.language English
dc.publisher KLUWER ACADEMIC PUBL
dc.subject Engineering
dc.title An industrial visual inspection system that uses inductive learning
dc.type Proceedings Paper
dc.identifier.volume 15
dc.identifier.startpage 569
dc.identifier.endpage 574
dc.contributor.department Sakarya Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü
dc.contributor.saüauthor Torkul, Orhan
dc.contributor.saüauthor Cedimoğlu, İsmail Hakkı
dc.relation.journal JOURNAL OF INTELLIGENT MANUFACTURING
dc.identifier.wos WOS:000222473500018
dc.contributor.author Torkul, Orhan
dc.contributor.author Cedimoğlu, İsmail Hakkı


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