Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning Methods
Nowadays machine learning and artificial neural networks are hot topic. These methods gains more and more ground in everyday life. In addition to everyday usage, an increasing emphasis placed on industrial use. In the field of research and development, materials science, robotics and thanks to the s...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Széchenyi István University
2019-10-01
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| Series: | Acta Technica Jaurinensis |
| Subjects: | |
| Online Access: | https://acta.sze.hu/index.php/acta/article/view/511 |
| _version_ | 1818976357951995904 |
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| author | Balázs Szűcs Áron Ballagi |
| author_facet | Balázs Szűcs Áron Ballagi |
| author_sort | Balázs Szűcs |
| collection | DOAJ |
| description | Nowadays machine learning and artificial neural networks are hot topic. These methods gains more and more ground in everyday life. In addition to everyday usage, an increasing emphasis placed on industrial use. In the field of research and development, materials science, robotics and thanks to the spread of Industry 4.0 and digitalization, more and more machine learning based systems introduced in production. This paper gives examples of possible ways of using machine learning algorithms in manufacturing, as well as reducing pseudo-error (false positive) rate of machine vision quality control systems. Even the simplest algorithms and models can be very effective on real-world problems. With the usage of convolutional neural networks, the pseudo-error rate of the examined system reducible. |
| first_indexed | 2024-12-20T16:10:34Z |
| format | Article |
| id | doaj.art-b87c863a41444d6ca734e3628096490f |
| institution | Directory Open Access Journal |
| issn | 2064-5228 |
| language | English |
| last_indexed | 2024-12-20T16:10:34Z |
| publishDate | 2019-10-01 |
| publisher | Széchenyi István University |
| record_format | Article |
| series | Acta Technica Jaurinensis |
| spelling | doaj.art-b87c863a41444d6ca734e3628096490f2022-12-21T19:33:59ZengSzéchenyi István UniversityActa Technica Jaurinensis2064-52282019-10-0112429430510.14513/actatechjaur.v12.n4.511511Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning MethodsBalázs Szűcs0Áron Ballagi1Audi Hungaria Zrt, Product Unit Diesel I4/V6, Audi Hungária út 1, H-9027 Győr, HungarySzéchenyi István University, Department of Automation, Egyetem tér 1, H-9026 Győr, HungaryNowadays machine learning and artificial neural networks are hot topic. These methods gains more and more ground in everyday life. In addition to everyday usage, an increasing emphasis placed on industrial use. In the field of research and development, materials science, robotics and thanks to the spread of Industry 4.0 and digitalization, more and more machine learning based systems introduced in production. This paper gives examples of possible ways of using machine learning algorithms in manufacturing, as well as reducing pseudo-error (false positive) rate of machine vision quality control systems. Even the simplest algorithms and models can be very effective on real-world problems. With the usage of convolutional neural networks, the pseudo-error rate of the examined system reducible.https://acta.sze.hu/index.php/acta/article/view/511machine learningclassificationconvolutional neural networkmachine visionindustry 4.0 |
| spellingShingle | Balázs Szűcs Áron Ballagi Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning Methods Acta Technica Jaurinensis machine learning classification convolutional neural network machine vision industry 4.0 |
| title | Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning Methods |
| title_full | Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning Methods |
| title_fullStr | Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning Methods |
| title_full_unstemmed | Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning Methods |
| title_short | Reducing Pseudo-error Rate of Industrial Machine Vision Systems with Machine Learning Methods |
| title_sort | reducing pseudo error rate of industrial machine vision systems with machine learning methods |
| topic | machine learning classification convolutional neural network machine vision industry 4.0 |
| url | https://acta.sze.hu/index.php/acta/article/view/511 |
| work_keys_str_mv | AT balazsszucs reducingpseudoerrorrateofindustrialmachinevisionsystemswithmachinelearningmethods AT aronballagi reducingpseudoerrorrateofindustrialmachinevisionsystemswithmachinelearningmethods |