rus
Issue #10/2023
I. Rozhkov, A. Garanin, D. Podolsky
CHASING EXCELLENCE: FROM DEEP MACHINE LEARNING TO ARTIFICIAL INTELLIGENCE IN MAKER-RAY AOI SYSTEMS. PART 1
CHASING EXCELLENCE: FROM DEEP MACHINE LEARNING TO ARTIFICIAL INTELLIGENCE IN MAKER-RAY AOI SYSTEMS. PART 1
DOI: 10.22184/1992-4178.2023.231.10.120.124
The introduction of deep machine learning methods in automatic optical inspection systems allowed Maker-Ray to create a machine that can self-learn, identify defects in printed circuit board mounting and, instead of an operator, is able to eliminate false positives. The article describes the problems of building a smart system for analyzing images of printed circuit boards.
The introduction of deep machine learning methods in automatic optical inspection systems allowed Maker-Ray to create a machine that can self-learn, identify defects in printed circuit board mounting and, instead of an operator, is able to eliminate false positives. The article describes the problems of building a smart system for analyzing images of printed circuit boards.
Теги: automatic optical inspection (aoi) component library component mounting defects deep machine learning false positives model автоматическая оптическая инспекция (аои) библиотека компонентов глубокое машинное обучение дефекты монтажа компонентов ложные срабатывания модель
CHASING EXCELLENCE: FROM DEEP MACHINE LEARNING TO ARTIFICIAL INTELLIGENCE IN MAKER-RAY AOI SYSTEMS. PART 1
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