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°Ë»ö°á°ú : 26
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ÇѱÛÁ¦¸ñ :
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[swµî·Ï] ÄÜÅÃÆ®·»Áî ºÒ·® ºÐ·ù AIµö·¯´× ¸ðµ¨ÇнÀ ÇÁ·Î±×·¥
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¿µ¹®Á¦¸ñ :
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[swµî·Ï] ÄÜÅÃÆ®·»Áî ºÒ·® ºÐ·ù AIµö·¯´× ¸ðµ¨ÇнÀ ÇÁ·Î±×·¥
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Çѱ¹ÀúÀÛ±ÇÀ§¿øȸ
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SWµî·Ï
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±è±â³²
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±è¼ºÈÆ, ÁÖÀÎ, ·ù°üÈñ
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ÄÜÅÃÆ®·»Áî, AIµö·¯´×, ¸ðµ¨ÇнÀ, ºÐ·® ºÐ·ù
ÄÜÅÃÆ®·»Áî, AIµö·¯´×, ¸ðµ¨ÇнÀ, ºÐ·® ºÐ·ù
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ȍȍ :
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ÇѱÛÁ¦¸ñ :
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Estimation of Machine Health Stability using Deep Learning
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¿µ¹®Á¦¸ñ :
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Estimation of Machine Health Stability using Deep Learning
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Àú³ÎÁ¤º¸ :
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BIGDAS2022
2022
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±¹¿ÜÇмú´ëȸ¹ßÇ¥³í¹®Áý
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chhol dimang
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¼ºêÀúÀÚ :
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±è¼ºÈÆ, ·ù°üÈñ
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Å°¿öµå :
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Machine Health Stability, Smart Factory, LSTM, GRU
Machine Health Stability, Smart Factory, LSTM, GRU
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ȍȍ :
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This research was supported by the MSS(Ministry of SMEs and Startups), Korea, under the Cloud-based customized smart factory big data platform research and development support program(S3290113) supervised by the TIPA(Korea Technology and Information Promotion Agency for SMEs) by the "Leaders in INdustry-university Cooperation 3.0" Project, supported by the Ministry of Education and National Research Foundation of Korea.
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ÇѱÛÁ¦¸ñ :
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Detection of bubble defects in contact lenses using YOLOv5
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¿µ¹®Á¦¸ñ :
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Detection of bubble defects in contact lenses using YOLOv5
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Àú³ÎÁ¤º¸ :
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BIGDAS2022
2022
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59
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63
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±¹¿ÜÇмú´ëȸ¹ßÇ¥³í¹®Áý
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±è¼ºÈÆ
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¼ºêÀúÀÚ :
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ÁÖÀÎ, ±è±â³², ·ù°üÈñ
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Å°¿öµå :
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deep-learning, contact-lens, object detection, smart factory
deep-learning, contact-lens, object detection, smart factory
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ȍȍ :
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This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program(IITP-2022-2020-0-01462) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation) and by the MSIT (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (2019-0- 01183) supervised by the IITP (Institute for Information & Communications Technology Planning & Evaluation).
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ÇѱÛÁ¦¸ñ :
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Measurement of Center Point Deviation for Detecting Contact Lens Defects
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¿µ¹®Á¦¸ñ :
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Measurement of Center Point Deviation for Detecting Contact Lens Defects
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Àú³ÎÁ¤º¸ :
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BIGDAS2022
2022
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12
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16
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125
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130
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±¹¿ÜÇмú´ëȸ¹ßÇ¥³í¹®Áý
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±è±â³²
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¼ºêÀúÀÚ :
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±è¼ºÈÆ, ÁÖÀÎ, ·ù°üÈñ
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Å°¿öµå :
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Contact lens, Hough Circle Transform, Gaussian Blur, Canny Edge Detection
Contact lens, Hough Circle Transform, Gaussian Blur, Canny Edge Detection
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ȍȍ :
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This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program(IITP-2022-2020- 0-01462) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation) and by the 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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ÇѱÛÁ¦¸ñ :
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Detecting small objects on a PCB using YoloV5
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¿µ¹®Á¦¸ñ :
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Detecting small objects on a PCB using YoloV5
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Àú³ÎÁ¤º¸ :
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BIGDAS2022
2022
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1
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±¹¿ÜÇмú´ëȸ¹ßÇ¥³í¹®Áý
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¸ÞÀÎÀúÀÚ :
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In Joo
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¼ºêÀúÀÚ :
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Sunghoon Kim, Ginam Kim, Kwan-Hee Yoo
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Å°¿öµå :
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process control block, artificial intelligence, data preprocessing, data augmentation, YoloV5
process control block, artificial intelligence, data preprocessing, data augmentation, YoloV5
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ȍȍ :
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This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program(IITP2022-2020-0-01462) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation)
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µö·¯´×À» ÀÌ¿ëÇÑ Ä«¸Þ¶ó ¸ðµâ ºÒ·® ºÐ·ù
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¿µ¹®Á¦¸ñ :
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Camera Module Defect Classification using Deep Learning
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Àú³ÎÁ¤º¸ :
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BIGDAS2022
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±èº´±Ù
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·ù°üÈñ
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Å°¿öµå :
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Deep Learning, Defect Classification, Resnet18
Deep Learning, Defect Classification, Resnet18
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ȍȍ :
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¡°º» ¿¬±¸´Â °úÇбâ¼úÁ¤º¸Åë½ÅºÎ ¹× Á¤º¸Åë½Å±âȹ Æò°¡¿øÀÇ Áö¿ªÁö´ÉÈÇõ½ÅÀÎÀç¾ç¼º(Grand ICT¿¬±¸ ¼¾ÅÍ) »ç¾÷ÀÇ ¿¬±¸°á°ú·Î ¼öÇàµÇ¾úÀ½¡± (IITP-2022-2020-0-01462)
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´ÙÀͽºÅ©¶ó ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇÑ ÈÀç Çdz ¹æÇ⠾ȳ» ½Ã½ºÅÛÀÇ °³¹ß
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¿µ¹®Á¦¸ñ :
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Development of a fire evacuation direction guidance system using Dijkstra Algor...
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BIGDAS2022
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°À±±¸
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·ù°üÈñ
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IoT, Disaster detection sensor
IoT, Disaster detection sensor
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¡Ø ¡°º» ¿¬±¸´Â °úÇбâ¼úÁ¤º¸Åë½ÅºÎ ¹× Á¤º¸Åë½Å ±âȹÆò°¡¿øÀÇ Áö¿ªÁö´ÉÈÇõ½ÅÀÎÀç¾ç¼º(Grand ICT ¿¬±¸¼¾ÅÍ) »ç¾÷ÀÇ ¿¬±¸°á°ú·Î ¼öÇàµÇ¾úÀ½¡± (IITP-2022-2020-0-01462)
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Effect of multimedia contents on the consumption of agricultural products: Focu...
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³ªÇüö
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±è±â³², ¾ÆÁöÁî ³ª½º¸®µð³ëÇÁ, ·ù°üÈñ
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³ó½ÄÇ° ¼Òºñ, ºòµ¥ÀÌÅÍ, ºñÁ¤Çü µ¥ÀÌÅÍ
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* º» ¿¬±¸´Â ³óÃÌÁøÈïû °øµ¿¿¬±¸»ç¾÷(°úÁ¦¹øÈ£: PJ015341012022)°ú Á¤ºÎ(±³À°ºÎ)ÀÇ Àç¿øÀ¸·Î Çѱ¹¿¬±¸Àç´ÜÀÇ Áö¿øÀ»(No. 2020R1I1A1A01071884) ¹Þ¾Æ ¼öÇàµÇ¾ú½À´Ï´Ù.
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ÇѱÛÁ¦¸ñ :
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Packaging Strategy for Data Analysis Modules
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¿µ¹®Á¦¸ñ :
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Packaging Strategy for Data Analysis Modules
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Àú³ÎÁ¤º¸ :
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THE KOREA CONTENTS ASSOCIATION
2022
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2
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281
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282
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±¹¿ÜÇмú´ëȸ¹ßÇ¥³í¹®Áý
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±è±â³²
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±è¼ºÈÆ, ÁÖÀÎ, Áö¼ö¿µ
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Å°¿öµå :
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Packaging, Data Analysis Module
Packaging Strategy for Data Analysis Modules
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ȍȍ :
|
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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[SWµî·Ï] Process Control Block »ý»ê ½Ç½Ã°£ ½Ã°¢È ÇÁ·Î±×·¥
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[SWµî·Ï] Process Control Block »ý»ê ½Ç½Ã°£ ½Ã°¢È ÇÁ·Î±×·¥
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Çѱ¹ÀúÀÛ±ÇÀ§¿øȸ
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SWµî·Ï
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ÁÖÀÎ
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±è¼ºÈÆ, ±è±â³², ·ù°üÈñ
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¹ÝµµÃ¼, °øÁ¤°úÁ¤, ½Ã°¢È, ºÒ·®, »ý»ê,
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