Abstract:The article is aimed at solving the problem of aerospace parts identification. A neural network model for part identification was developed. The proposed model consists of three modules: object detection using the YOLO3 model, preprocessing of the selected fragment, and classification of the processed fragment using the VGG19 model. A distinctive feature of the developed model is the use of STL objects for training the VGG19 neural network. To increase the reliability of the classification for each object we u… Show more
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