DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-6,Issue-8 ( Aug, 2019 ) | |||||||||
Paper Title |
Implementation of Artificial Intelligence to Detect Images in The Manufacturing Process | |||||||||
Author Name |
Marek Kocisko, Juraj Kundrik, Martin Pollak, Monika Teliskova | |||||||||
Affilition |
Technical university of Košice, Faculty of manufacturing technologies with a seat in Prešov Slovakia | |||||||||
Pages |
1-4 | |||||||||
Abstract |
Automation of the production of ever more complex products brings along an increase in product control requirements. In addition, industry, especially automotive, requires a further increase in production accuracy, minimization of downtime and delivery by just-in-time. Quality control by accidental selection and by mechanical devices is not sufficient to meet the production requirements. In most cases, visual quality control is ensured by people. This article describes the basic paradigms of using artificial intelligence systems for quality control detection. To describe the deployment techniques of artificial intelligence elements, the RetinaNet Convoluntary Neural Network (CNN) was used. Keywords - Neural Networks, Quality Control, Error Detection. | |||||||||
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