ITM Web Conf.
Volume 30, 201929th International Crimean Conference “Microwave & Telecommunication Technology” (CriMiCo’2019)
|Number of page(s)||4|
|Section||Information Technology in Telecommunications (3a)|
|Published online||27 November 2019|
Algorithm for automated visual inspection of MMIC using a classifier based on neural networks
1 Joint-stock Company “Research Institute of Semiconductor Devices”, 634034 Tomsk, Russia
2 Tomsk State University of Control Systems and Radioelectronics, 634050 Tomsk, Russia
* Corresponding author: shiryaev firstname.lastname@example.org
We present the algorithm for automated visual inspection of microwave monolithic integrated circuits (MMIC) using computer vision and artificial neural networks. The artificial neural network classifies each pixel of a microphotograph to a certain photomask area. The algorithm detects defectiveness of an MMIC according to classification result and photomask comparison.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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