Algorithm for automated visual inspection of monolithic integrated circuits using neural networks
DOI: 10.21293/1818-0442-2019-22-2-72-76
Abstract: The article describes the problem of visual control in the production of MMIC. The algorithm for automated visual control is implemented using neural networks. The neural network performs a parallel analysis of micrograph and photo-mask device. Then it outputs information about the defectiveness of the device. Thus, the speed of visual control of MMIC increases without losing the quality of defect detection.
Keywords: automation, mmic, convolutional neural networks
Authors and copyright holders:
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For citation:
Shiryaev B. V., Yuschenko A. Yu., Bezruk A. V. Algorithm for automated visual inspection of monolithic integrated circuits using neural networks. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2019, vol. 22, no. 2, pp. 72–76. DOI: 10.21293/1818-0442-2019-22-2-72-76
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