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2021 연구성과별 연구자 정보 (527 / 2991)

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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 Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study Kim, Jin Young Kim, JY 6 Keimyung Univ, Dongsan Hosp, Dept Radiol, Daegu, South Korea CAI-2335-2022 Lee, Jun Young 0000-0001-6714-8358 Kim, Jin Young s-choi@knu.ac.kr;
Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study Kim, Ki Beom Kim, KB 7 Daegu Fatima Hosp, Dept Radiol, Daegu, South Korea 0000-0003-4508-6058 Kim, Ki Beom s-choi@knu.ac.kr;
Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study Choi, Sooyoung Choi, S 8 교신저자 Yeungnam Univ, Dept Radiol, Med Ctr, Daegu, South Korea 0000-0003-1313-1002 Choi, Sooyoung s-choi@knu.ac.kr;
Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study Kim, Young Hwan Kim, YH 9 Daegu Catholic Univ, Sch Med, Dept Radiol, Daegu, South Korea s-choi@knu.ac.kr;
Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study Lim, Jae-Kwang Lim, JK 10 Kyungpook Natl Univ, Sch Med, Dept Radiol, Daegu, South Korea 0000-0002-1299-9996 Lim, Jae-Kwang s-choi@knu.ac.kr;
Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study Choi, Sanghun Choi, S 11 교신저자 Kyungpook Natl Univ, Sch Mech Engn, 80 Daehak Ro, Daegu 41566, South Korea AGS-7430-2022 Choi, Sanghun s-choi@knu.ac.kr;
Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study Kim, Taewoo Kim, T 1 Kyungpook Natl Univ, Sch Mech Engn, 80 Daehak Ro, Daegu 41566, South Korea s-choi@knu.ac.kr;
Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study Lee, Dong Hyun Lee, DH 2 Good Gang An Hosp, Div Gastroenterol, Dept Internal Med, Busan, South Korea 0000-0003-2585-2894 Lee, Dong Hyun s-choi@knu.ac.kr;
Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study Park, Eun-Kee Park, EK 3 Kosin Univ, Dept Med Humanities & Social Med, Coll Med, Busan, South Korea s-choi@knu.ac.kr;
Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study Choi, Sanghun Choi, S 4 교신저자 Kyungpook Natl Univ, Sch Mech Engn, 80 Daehak Ro, Daegu 41566, South Korea AGS-7430-2022 Choi, Sanghun 0000-0001-5030-0296 Choi, Sanghun s-choi@knu.ac.kr;
Deep Learning-Based Automatic Modulation Classification With Blind OFDM Parameter Estimation Park, Myung Chul Park, MC 1 Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea 0000-0001-6287-9071 Park, Myung Chul dshan@knu.ac.kr;
Deep Learning-Based Automatic Modulation Classification With Blind OFDM Parameter Estimation Han, Dong Seog Han, DS 2 교신저자 Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea N-8949-2018 Han, Dong Seog 0000-0002-7769-0236 Han, Dong Seog dshan@knu.ac.kr;
Deep Learning-Based Method to Recognize Line Objects and Flow Arrows from Image-Format Piping and Instrumentation Diagrams for Digitization Moon, Yoochan Moon, Y 1 Korea Univ, Sch Mech Engn, 145 Anam Ro, Seoul 02841, South Korea ans9173@korea.ac.kr;jinwonlee@korea.ac.kr;dhmun@korea.ac.kr;sea3729@naver.com;
Deep Learning-Based Method to Recognize Line Objects and Flow Arrows from Image-Format Piping and Instrumentation Diagrams for Digitization Lee, Jinwon Lee, J 2 Korea Univ, Sch Mech Engn, 145 Anam Ro, Seoul 02841, South Korea JZS-9570-2024 Lee, Jinwon 0000-0003-4810-1014 Lee, Jinwon ans9173@korea.ac.kr;jinwonlee@korea.ac.kr;dhmun@korea.ac.kr;sea3729@naver.com;
Deep Learning-Based Method to Recognize Line Objects and Flow Arrows from Image-Format Piping and Instrumentation Diagrams for Digitization Mun, Duhwan Mun, D 3 교신저자 Korea Univ, Sch Mech Engn, 145 Anam Ro, Seoul 02841, South Korea AAC-5360-2020 Mun, Duhwan 0000-0002-5477-0671 Mun, Duhwan ans9173@korea.ac.kr;jinwonlee@korea.ac.kr;dhmun@korea.ac.kr;sea3729@naver.com;
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