The Impact of a Number of Samples on Unsupervised Feature Extraction, Based on Deep Learning for Detection Defects in Printed Circuit Boards
Deep learning provides new ways for defect detection in automatic optical inspections (AOI). However, the existing deep learning methods require thousands of images of defects to be used for training the algorithms. It limits the usability of these approaches in manufacturing, due to lack of images...
Main Authors: | Ihar Volkau, Abdul Mujeeb, Wenting Dai, Marius Erdt, Alexei Sourin |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-12-01
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Series: | Future Internet |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-5903/14/1/8 |
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