Characterization of MEMS comb capacitor

Ahmad, Farooq; Baig, Athar; Dennis, John Ojur; Hamid, Nor Hisham; Khir, M. H. Md

doi:10.1007/s00542-019-04671-1

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2022

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Cited by 2 publications

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“…A microelectromechanical system (MEMS) is miniaturized, compact, inexpensive, easy to integrate, and compatible with the standard process [ 1 ]. It has been widely used in industrial productions [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Defect Inspection System Using Convolutional Neural Network for MEMS Pressure Sensors

Deng

Zhang

et al. 2022

J. Imaging

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Defect inspection using imaging-processing techniques, which detects and classifies manufacturing defects, plays a significant role in the quality control of microelectromechanical systems (MEMS) sensors in the semiconductor industry. However, high-precision classification and location are still challenging because the defect images that can be obtained are small and the scale of the different defects on the picture of the defect is different. Therefore, a simple, flexible, and efficient convolutional neural network (CNN) called accurate-detection CNN (ADCNN) to inspect MEMS pressure-sensor-chip packaging is proposed in this paper. The ADCNN is based on the faster region-based CNN, which improved the performance of the network by adding random-data augmentation and defect classifiers. Specifically, the ADCNN achieved a mean average precision of 92.39% and the defect classifier achieved a mean accuracy of 97.2%.

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Section: Introductionmentioning

confidence: 99%