Accuracy Improvement by Artificial Neural Networks in Technical Vision System
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
Authors
This paper proposes an Artificial Neural Network (ANN) to accurately predict the real angles obtained by a Triangulation Vision System. The performance of the ANN is compared with the K-Nearest Neighbors algorithm from previous publications. For the experimentation it was necessary to create a database to train and prove both methods in different coordinates on a determinate area through the dynamic triangulation method. Afterwards, the root mean square error is calculated to obtain the accuracy of each algorithm. Finally, several laser scanning measurements were taken at different distances to analyze the measurement dispersion of both algorithms.
Originalsprache | Englisch |
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Titel | IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society |
Anzahl der Seiten | 6 |
Erscheinungsort | Piscataway |
Verlag | IEEE - Institute of Electrical and Electronics Engineers Inc. |
Erscheinungsdatum | 10.2019 |
Seiten | 5572-5577 |
Aufsatznummer | 8927596 |
ISBN (Print) | 978-1-7281-4879-3 |
ISBN (elektronisch) | 978-1-7281-4878-6 |
DOIs | |
Publikationsstatus | Erschienen - 10.2019 |
Veranstaltung | 45th Annual Conference of the Institute of Electrical and Electronics Engineers' Industrial Electronics Society - 2019 - Lisbon Congress Center, Lisbon, Portugal Dauer: 14.10.2019 → 17.10.2019 Konferenznummer: 45 https://iecon2019.org/ |
- Ingenieurwissenschaften