| Issue |
ITM Web Conf.
Volume 30, 2019
29th International Crimean Conference “Microwave & Telecommunication Technology” (CriMiCo’2019)
|
|
|---|---|---|
| Article Number | 04012 | |
| Number of page(s) | 4 | |
| Section | Information Technology in Telecommunications (3a) | |
| DOI | https://doi.org/10.1051/itmconf/20193004012 | |
| 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 bv@niipp.ru
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.