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http://hdl.handle.net/20.500.12188/25341
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Markovski, Gjorgji | en_US |
dc.contributor.author | Djinevski, Leonid | en_US |
dc.contributor.author | Chungurski, Slavcho | en_US |
dc.contributor.author | Stojanovski, Toni | en_US |
dc.date.accessioned | 2023-01-10T08:18:55Z | - |
dc.date.available | 2023-01-10T08:18:55Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/25341 | - |
dc.description.abstract | Aeronautical navigation datais discussed and possible issues regarding obtaining the source information is presented. AI algorithms for object recognition as presented in order to provide an automated approach for extracting publicly available information that is provided in image formats. The results prove a large accuracy for recognizing aeronautical data. | en_US |
dc.subject | AI, Neural Networks, Object Recognition, YOLO, SSD | en_US |
dc.title | AeronauticalObject Recognitionusing Neural Network Algorithms | en_US |
dc.type | Proceedings | en_US |
dc.relation.conference | ICT Innovations | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
Files in This Item:
File | Опис | Size | Format | |
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aeronauticalobject-recognitionusing-neural-network-algorithms.pdf | 434.36 kB | Adobe PDF | View/Open |
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