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2022 연구성과별 연구자 정보 (680 / 2879)
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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 Approach for Improving Spectral Efficiency in mmWave Hybrid Beamforming Systems | Son, Woosung | Son, W | 1 | 교신저자 | Kyungpook Natl Univ, Grad Sch Elect & Elect Engn, Daegu, South Korea | sonws1230@knu.ac.kr;dshan@knu.ac.kr; | ||||
| Deep Learning Approach for Improving Spectral Efficiency in mmWave Hybrid Beamforming Systems | Han, Dong Seog | Han, DS | 2 | Kyungpook Natl Univ, Sch Elect Engn, Daegu, South Korea | sonws1230@knu.ac.kr;dshan@knu.ac.kr; | |||||
| Deep Learning Ensemble-Based Automated and High-Performing Recognition of Coffee Leaf Disease | Novtahaning, Damar | Novtahaning, D | 1 | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea | MBG-8072-2025 | Novtahaning, Damar | 0000-0003-3218-410X | Novtahaning, Damar | jmkang@knu.ac.kr; | |
| Deep Learning Ensemble-Based Automated and High-Performing Recognition of Coffee Leaf Disease | Shah, Hasnain Ali | Shah, HA | 2 | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea | 0000-0001-5325-9014 | Shah, Hasnain Ali | jmkang@knu.ac.kr; | |||
| Deep Learning Ensemble-Based Automated and High-Performing Recognition of Coffee Leaf Disease | Kang, Jae-Mo | Kang, JM | 3 | 교신저자 | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea | 0000-0002-8181-5994 | Kang, Jae-Mo | jmkang@knu.ac.kr; | ||
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Ryu, Jeong Yeop | Ryu, JY | 1 | Kyungpook Natl Univ, Sch Med, Dept Plast & Reconstruct Surg, Daegu 41944, South Korea | GLQ-9419-2022 | Ryu, Jeong Yeop | 0000-0003-2812-5051 | Ryu, Jeong Yeop | hy-chung@knu.ac.kr; | |
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Hong, Hyun Ki | Hong, HK | 2 | Kyungpook Natl Univ, Sch Med, Dept Plast & Reconstruct Surg, Daegu 41944, South Korea | 0000-0001-6922-0691 | Hong, Hyun Ki | hy-chung@knu.ac.kr; | |||
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Cho, Hyun Geun | Cho, HG | 3 | Kyungpook Natl Univ, Sch Med, Dept Plast & Reconstruct Surg, Daegu 41944, South Korea | 0000-0003-3851-0623 | Cho, HyunGeun | hy-chung@knu.ac.kr; | |||
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Lee, Joon Seok | Lee, JS | 4 | Kyungpook Natl Univ, Sch Med, Dept Plast & Reconstruct Surg, Daegu 41944, South Korea | Q-3108-2018 | LEE, JIN | hy-chung@knu.ac.kr; | |||
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Yoo, Byeong Cheol | Yoo, BC | 5 | DEEPNOID Co, Seoul 08376, South Korea | hy-chung@knu.ac.kr; | |||||
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Choi, Min Hyeok | Choi, MH | 6 | DEEPNOID Co, Seoul 08376, South Korea | hy-chung@knu.ac.kr; | |||||
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Chung, Ho Yun | Chung, HY | 7 | 교신저자 | Kyungpook Natl Univ, Sch Med, Dept Plast & Reconstruct Surg, Daegu 41944, South Korea | 0000-0001-7359-3044 | Chung, Ho Yun | hy-chung@knu.ac.kr; | ||
| Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net | Chung, Ho Yun | Chung, HY | 7 | 교신저자 | Kyungpook Natl Univ, Sch Med, Cell & Matrix Res Inst, Daegu 41944, South Korea | 0000-0001-7359-3044 | Chung, Ho Yun | hy-chung@knu.ac.kr; | ||
| Deep Learning Provides Substantial Improvements to County-Level Fire Weather Forecasting Over the Western United States | Son, Rackhun | Son, R | 1 | Max Planck Inst Biogeochem Jena, Dept Biogeochem Integrat, Jena, Germany | 0000-0002-3366-495X | Son, Rackhun | yjinho@gist.ac.kr; | |||
| Deep Learning Provides Substantial Improvements to County-Level Fire Weather Forecasting Over the Western United States | Son, Rackhun | Son, R | 1 | Gwangju Inst Sci & Technol, Sch Earth Sci & Environm Engn, Gwangju, South Korea | 0000-0002-3366-495X | Son, Rackhun | yjinho@gist.ac.kr; |
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