Please use this identifier to cite or link to this item:
http://cmuir.cmu.ac.th/jspui/handle/6653943832/70435
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Autanan Wannachai | en_US |
dc.contributor.author | Wanarut Boonyung | en_US |
dc.contributor.author | Paskorn Champrasert | en_US |
dc.date.accessioned | 2020-10-14T08:30:54Z | - |
dc.date.available | 2020-10-14T08:30:54Z | - |
dc.date.issued | 2020-01-01 | en_US |
dc.identifier.issn | 18678211 | en_US |
dc.identifier.other | 2-s2.0-85089721158 | en_US |
dc.identifier.other | 10.1007/978-3-030-57115-3_5 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85089721158&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/70435 | - |
dc.description.abstract | © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Typically, manufacturing machines represent their working status via the seven-segment LED display. The operators have to read the machine working status periodically. The process information time-lagging and human-error may occur. These causes may defect the output products and reduce manufacturing productivity. This research paper proposes a real-time and automatic machine display tracking system. The proposed real-time seven-segment LED display recognition system is designed to apply to the actual machines in the manufacturing. However, the camera installation problem degrades the image qualities such as machine vibration, light reflection, brightness, and camera view’s frame changes. The proposed Real-time Sevens segment Display detection and recognition online system using CNN (RSDC) consists of the camera controller module and the Interpretation of Seven-Segment display (ISS) framework. The RSDC can track the machine’s display and interpret the camera images to numerical data using the machine learning technique to handle the installation problems. The experiment result shows that the proposed ISS framework has an interpretation accuracy of 91.1%. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Real-Time Seven Segment Display Detection and Recognition Online System Using CNN | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST | en_US |
article.volume | 329 LNICST | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
Files in This Item:
There are no files associated with this item.
Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.