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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
Deep metric learning-based image retrieval system for chest radiograph and its clinical applications in COVID-19 Li, Quanzheng Li, QZ 20 교신저자 MGH & BWH Ctr Clin Data Sci, Boston, MA 02114 USA li.quanzheng@mgh.harvard.edu;
Deep visual domain adaptation and semi-supervised segmentation for understanding wave elevation using wave flume video images Kim, Jinah Kim, J 1 교신저자 Korea Inst Ocean Sci & Technol, Coastal Disaster Res Ctr, Busan 49111, South Korea jaeilkim@knu.ac.kr;
Deep visual domain adaptation and semi-supervised segmentation for understanding wave elevation using wave flume video images Kim, Taekyung Kim, T 2 Korea Inst Ocean Sci & Technol, Coastal Disaster Res Ctr, Busan 49111, South Korea jaeilkim@knu.ac.kr;
Deep visual domain adaptation and semi-supervised segmentation for understanding wave elevation using wave flume video images Oh, Sang-Ho Oh, SH 3 Changwon Natl Univ, Dept Civil Engn, Changwon Si 51140, South Korea ISV-3878-2023 Oh, Sang Ho jaeilkim@knu.ac.kr;
Deep visual domain adaptation and semi-supervised segmentation for understanding wave elevation using wave flume video images Do, Kideok Do, K 4 Korea Maritime & Ocean Univ, Dept Ocean Engn, Busan 49111, South Korea AHD-8394-2022 Do, Kideok jaeilkim@knu.ac.kr;
Deep visual domain adaptation and semi-supervised segmentation for understanding wave elevation using wave flume video images Ryu, Joon-Gyu Ryu, JG 5 Elect & Telecommun Res Inst, Satellite Wide Area Infra Res Sect, Daejeon 34129, South Korea jaeilkim@knu.ac.kr;
Deep visual domain adaptation and semi-supervised segmentation for understanding wave elevation using wave flume video images Kim, Jaeil Kim, J 6 교신저자 Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea jaeilkim@knu.ac.kr;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Jeon, Su-Jin Jeon, SJ 1 Wonkwang Univ, Dept Conservat Dent, Daejeon Dent Hosp, Daejeon, South Korea profee@naver.com;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Yun, Jong-Pil Yun, JP 2 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea profee@naver.com;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Yeom, Han-Gyeol Yeom, HG 3 Wonkwang Univ, Dept Oral & Maxillofacial Radiol, Daejeon Dent Hosp, Daejeon, South Korea profee@naver.com;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Shin, Woo-Sang Shin, WS 4 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea profee@naver.com;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Shin, Woo-Sang Shin, WS 4 Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daegu, South Korea profee@naver.com;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Lee, Jong-Hyun Lee, JH 5 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea ABE-6242-2020 Lee, jaeho profee@naver.com;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Lee, Jong-Hyun Lee, JH 5 Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daegu, South Korea ABE-6242-2020 Lee, jaeho profee@naver.com;
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs Jeong, Seung-Hyun Jeong, SH 6 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea profee@naver.com;
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