Defect Detection of MEMS Based on Data Augmentation, WGAN-DIV-DC, and a YOLOv5 Model

Surface defect detection of micro-electromechanical system (MEMS) acoustic thin film plays a crucial role in MEMS device inspection and quality control. The performances of deep learning object detection models are significantly affected by the number of samples in the training dataset. However, it...

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Detalles Bibliográficos
Autores principales: Shi, Zhenman, Sang, Mei, Huang, Yaokang, Xing, Lun, Liu, Tiegen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739821/
https://www.ncbi.nlm.nih.gov/pubmed/36502102
http://dx.doi.org/10.3390/s22239400

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739821/
https://www.ncbi.nlm.nih.gov/pubmed/36502102
http://dx.doi.org/10.3390/s22239400

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