Defect detection of mems based on data augmentation, wgan-div-dc, and a yolov5 model

HIGHLIGHTS

• who: Zhenman Shi and colleagues from the School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, China have published the research work: Defect Detection of MEMS Based on Data Augmentation, WGAN-DIV-DC, and a YOLOv5 Model, in the Journal: Sensors 2022, 9400 of /2022/
• what: The authors provide a brief overview of previous studies related to data augmentation with GANs, and then the authors discuss the relevant work on object detection with single-stage and two-stage models. The experiments showed that the GAN could enhance the diversity of defects, which improved . . .
  

   

  

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