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NTIS 바로가기반도체디스플레이기술학회지 = Journal of the semiconductor & display technology, v.21 no.3, 2022년, pp.63 - 68
In this study, we produced defect detection models using parallel convolution neural networks. If convolution neural networks are constructed parallel type, the model's detection accuracy will increase and detection time will decrease. We produced parallel-type defect detection models using 4 types ...
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Song-Yeon Lee and Yong-Jeong Huh, "A Study on Surface Defect Detection Model of 3D Printing Bone Plate Using Deep Learning Algorithm", J. of The Korean Society of Semiconductor & Display Technology, Vol.20, pp. 68-73, 2021.
Gee-Yeun Kim and Hyoung-Gook Kim, "Performanc Comparison of Lung Sound Classification Using Various Convolutional Neural Networks," J. of The Acoustical Society of Korea, Vol. 38, pp. 568-573, 2019.
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Jun-Hee Jung and Joong-Hwee Cho, "A Through-focus Scanning Optical Microscopy Dimensional Measurement Method based on A Deep-learning Regression Model", J. of The Korean Society of Semiconductor & Display Technology, Vol.21, pp. 108-113, 2022.
Se-Rang Oh and Young-Chul Bae, "Braille Block Recognition Algorithm for the Visually Impaired Based on YOLO V3", J. of The Korean Institute of Intelligent Systems, Vol.31, pp. 60-67, 2021.
Song-Yeon Lee and Yong-Jeong Huh, "A Study on Shape Warpage Defect Detection Medel of Scaffold Using Deep Learning Base CNN", J. of The Korean Society of Semiconductor & Display Technology, Vol.20, pp. 99-103, 2021.
Ji-Soo Kang, Se-Eun Shim, Sun-Moon Jo and Kyung-Yong Chung, "YOLO based Light Source Object Detection for Traffic Image Big Data Processing", J. of The Korean Convergence for Information Technology, Vol.10, pp. 40-46, 2020.
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