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SUNGHOON KIM, GINAM KIM, KWAN-HEE YOO
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Defect detection, feature fusion, feature pyramid, printed circuit board (PCB), small object detection, small object information flow (SOIF-DN), deep learning
Defect detection, feature fusion, feature pyramid, printed circuit board (PCB), small object detection, small object information flow (SOIF-DN), deep learning
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This work was supported in part by the Ministry of Science and Information Communication Technology (MSIT), South Korea, through the Grand Information Technology Research Center Support Program, Supervised by the Institute for Information and Communications Technology Planning and Evaluation (IITP), under Grant IITP-2023-2020-0-01462.
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The Characteristic Data of Middle School Students in Eup and Myeon Units, Machine Learning, Predict Students Entrance into High School, Accuracy∣
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º» ¿¬±¸´Â °úÇбâ¼úÁ¤º¸Åë½ÅºÎ ¹× Á¤º¸Åë½Å±âȹÆò°¡¿øÀÇ Áö¿ªÁö´ÉÈÇõ½ÅÀÎÀç¾ç¼º(Grand ICT¿¬±¸¼¾ÅÍ) »ç¾÷ÀÇ ¿¬±¸°á°ú·Î ¼ö ÇàµÇ¾úÀ½¡± (IITP-2023-2020-0-01462)
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Ga-Ae Ryu
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Tserenpurev Chuluunsaikhan, Aziz Nasridinov, HyungChul Rah and Kwan-Hee Yoo
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sparse critical event-driven LSTM (SCE-LSTM); forecasting; pork consumption; unstructured big data
sparse critical event-driven LSTM (SCE-LSTM); forecasting; pork consumption; unstructured big data
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ȍȍ :
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This work has been supported by the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2023-2020-0-01462) su- pervised by the IITP (Institute for Information & communications Technology Planning & Evalua- tion), and the Basic Science Research Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant number:2020R1I1A1A01071884).
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packaging method
packaging method
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This work was supported by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (No. P0022332, Digital data platform for material development)
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ELSEVIER
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SCI(E)
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¸ÞÀÎÀúÀÚ :
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Jeong-Hun Kim, Hyunseok Ko
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Dong-Hun Yeo. Zeehoon Park, Upendra Kumar, Kwan-Hee Yoo, Aziz Nasridinov, Sung Beom Cho
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Machine learning Simulation Data deficiency Inverse design Tape-casting
Machine learning Simulation Data deficiency Inverse design Tape-casting
|
ȍȍ :
|
We acknowledge the support from Ministry of Trade, Industry & Energy (20004367) and National Research Foundation (RS-2023- 00209910). This research was also supported by the MSIT(Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program(IITP-2023-2020-0-01462) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation). The computations were carried out using re- sources from Korea Supercomputing Center (KSC-2022-CRE-0348).
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The Smart Factory with Variable System Design
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The Smart Factory with Variable System Design
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Chae-Hyun Lee
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Sung-Jin Im, Ja-Yeon Heo, Jin-Soo Kim and Kwan-Hee Yoo
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Smart Factory, MongoDB, Dynamic, Real Time
Smart Factory, MongoDB, Dynamic, Real Time
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ȍȍ :
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This work was partly supported by the Technology development Program of MSS S3290113 and the ICT development R&D program of MSIT S3290113
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