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http://dx.doi.org/10.9717/kmms.2020.24.3.382

Coreset Construction for Character Recognition of PCB Components Based on Deep Learning  

Gang, Su Myung (Dept of Computer Engineering, Graduate School, Keimyung University)
Lee, Joon Jae (Faculty of Computer Engineering, Keimyung University)
Publication Information
Journal of Korea Multimedia Society / v.24, no.3, 2021 , pp. 382-395 More about this Journal
Abstract
In this study, character recognition using deep learning is performed among the various defects in the PCB, the purpose of which is to check whether the printed characters are printed correctly on top of components, or the incorrect parts are attached. Generally, character recognition may be perceived as not a difficult problem when considering MNIST, but the printed letters on the PCB component data are difficult to collect, and have very high redundancy. So if a deep learning model is trained with original data without any preprocessing, it can lead to over fitting problems. Therefore, this study aims to reduce the redundancy to the smallest dataset that can represent large amounts of data collected in limited production sites, and to create datasets through data enhancement to train a flexible deep learning model can be used in various production sites. Moreover, ResNet model verifies to determine which combination of datasets is the most effective. This study discusses how to reduce and augment data that is constantly occurring in real PCB production lines, and discusses how to select coresets to learn and apply deep learning models in real sites.
Keywords
Deep Learning; Coreset; PCB Inspection; OCR; ResNet;
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