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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 applications on satellite imagery datasets for nuclear nonproliferation and counter-proliferation Ha, Gayeon Ha, G 2 Korea Inst Nucl Nonproliferat & Control, 1418 Yuseong Daero, Daejeon, South Korea ars@knu.ac.kr;
Deep learning applications on satellite imagery datasets for nuclear nonproliferation and counter-proliferation Han, Youkyung Han, Y 3 Seoul Natl Univ Sci & Technol, Dept Civil Engn, 232 Gongneung Ro, Seoul, South Korea ars@knu.ac.kr;
Deep learning applications on satellite imagery datasets for nuclear nonproliferation and counter-proliferation Lee, Changhui Lee, C 4 Seoul Natl Univ Sci & Technol, Dept Civil Engn, 232 Gongneung Ro, Seoul, South Korea ars@knu.ac.kr;
Deep learning applications on satellite imagery datasets for nuclear nonproliferation and counter-proliferation Lee, Hyunjin Lee, H 5 Seoul Natl Univ Sci & Technol, Dept Civil Engn, 232 Gongneung Ro, Seoul, South Korea ars@knu.ac.kr;
Deep learning applications on satellite imagery datasets for nuclear nonproliferation and counter-proliferation Song, Ahram Song, A 6 교신저자 Kyungpook Natl Univ, Dept Locat Based Informat Syst, 2559 Gyeongsang Daero, Sangju, South Korea ars@knu.ac.kr;
Deep learning approaches for bruised mandarin orange classification by fluorescence hyperspectral imaging Lee, Ahyeong Lee, A 1 Natl Inst Agr Sci, Dept Agr Engn, 310 Nongsaengmyeong Ro, Jeonju 54875, South Korea hsj5596@knu.ac.kr; moon.kim@usda.gov;
Deep learning approaches for bruised mandarin orange classification by fluorescence hyperspectral imaging Baek, Insuck Baek, I 2 ARS, USDA, Environm Microbial & Food Safety Lab, 10300 Baltimore Ave, Beltsville, MD 20705 USA hsj5596@knu.ac.kr; moon.kim@usda.gov;
Deep learning approaches for bruised mandarin orange classification by fluorescence hyperspectral imaging Kim, Jinse Kim, J 3 Natl Inst Agr Sci, Dept Agr Engn, 310 Nongsaengmyeong Ro, Jeonju 54875, South Korea hsj5596@knu.ac.kr; moon.kim@usda.gov;
Deep learning approaches for bruised mandarin orange classification by fluorescence hyperspectral imaging Hong, Suk-Ju Hong, SJ 4 교신저자 Natl Inst Agr Sci, Dept Agr Engn, 310 Nongsaengmyeong Ro, Jeonju 54875, South Korea hsj5596@knu.ac.kr; moon.kim@usda.gov;
Deep learning approaches for bruised mandarin orange classification by fluorescence hyperspectral imaging Hong, Suk-Ju Hong, SJ 4 교신저자 Kyungpook Natl Univ, Dept Smart Bioind Mech Engn, Daegu 41566, South Korea hsj5596@knu.ac.kr; moon.kim@usda.gov;
Deep learning approaches for bruised mandarin orange classification by fluorescence hyperspectral imaging Kim, Moon S. Kim, MS 5 교신저자 ARS, USDA, Environm Microbial & Food Safety Lab, 10300 Baltimore Ave, Beltsville, MD 20705 USA hsj5596@knu.ac.kr; moon.kim@usda.gov;
Deep learning for NAD/NADP cofactor prediction and engineering using transformer attention analysis in enzymes Kim, Jaehyung Kim, J 1 Ulsan Natl Inst Sci & Technol UNIST, Sch Energy & Chem Engn, Ulsan 44919, South Korea dkim@unist.ac.kr;
Deep learning for NAD/NADP cofactor prediction and engineering using transformer attention analysis in enzymes Woo, Jihoon Woo, J 2 Ulsan Natl Inst Sci & Technol UNIST, Sch Energy & Chem Engn, Ulsan 44919, South Korea dkim@unist.ac.kr;
Deep learning for NAD/NADP cofactor prediction and engineering using transformer attention analysis in enzymes Park, Joon Young Park, JY 3 Ulsan Natl Inst Sci & Technol UNIST, Sch Energy & Chem Engn, Ulsan 44919, South Korea dkim@unist.ac.kr;
Deep learning for NAD/NADP cofactor prediction and engineering using transformer attention analysis in enzymes Kim, Kyung-Jin Kim, KJ 4 Kyungpook Natl Univ, KNU Inst Microbiol, Sch Life Sci, BK21 FOUR KNU Creat Biores Grp, Daegu 41566, South Korea MVY-3405-2025 Kim, Kyung-Jin dkim@unist.ac.kr;
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