Augmented Reality Maintenance Assistant Using YOLOv5
نویسندگان
چکیده
Maintenance professionals and other technical staff regularly need to learn identify new parts in car engines equipment. The present work proposes a model of task assistant based on deep learning neural network. A YOLOv5 network is used for recognizing some the constituent an automobile. dataset engine images was created eight were marked images. Then, trained detect each part. results show that YOLOv5s able successfully real time video streams, with high accuracy, thus being useful as aid train deal equipment using augmented reality. architecture object recognition system reality glasses also designed.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2021
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app11114758