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2024 연구자 정보 (1064 / 1079)

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Author Name 제1저자 여부 ⓘ 교신저자 여부 ⓘ Address ResearcherID ORCID Paper Title WoS Edition 최상위 JCR(%) WoS Category Related Email
Choi, Min-Kook
(Choi, MK) ⓘ 		Hutom, Seoul, South Korea ⓘ ABE-2827-2020
Choi, Min-Kook ⓘ
ⓘ 		Towards Precise Pose Estimation in Robotic Surgery: Introducing Occlusion-Aware Loss ⓘ ⓘ ⓘ jihun1142@knu.ac.kr;heechul@knu.ac.kr; ⓘ
Choi, Seung Hun
(Choi, SH) ⓘ 		제1저자 교신저자 Korea Univ, Dept Comp Sci & Engn, Seoul, South Korea ⓘ
ⓘ
ⓘ 		ComBoost: An Instruction Complexity Aware DTM Technique for Edge Devices
Sparrow ECC: A Lightweight ECC Approach for HBM Refresh Reduction towards Energy-efficient DNN Inference ⓘ 		ⓘ ⓘ csh30096@korea.ac.kr;joonho.kong@knu.ac.kr;swchung@korea.ac.kr;
thomas1324@korea.ac.kr;csh30096@korea.ac.kr;yhgong@ssu.ac.kr;joonho.kong@knu.ac.kr;swchung@korea.ac.kr; ⓘ
Choi, Sun Hee
(Choi, SH) ⓘ 		Kyung Hee Univ, Sch Med, Dept Pediat, Seoul, South Korea ⓘ
ⓘ
ⓘ 		Allergic rhinitis and hygiene hypothesis ⓘ ⓘ ⓘ pymcko@gmail.com; ⓘ
Choi, Yera
(Choi, Y) ⓘ 		NAVER Cloud, NAVER AI LAB, NAVER Digital Healthcare LAB, Seoul, South Korea ⓘ
ⓘ
ⓘ 		BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification ⓘ ⓘ ⓘ kaen2891@knu.ac.kr;seongeun.moon@navercorp.com;hoyjung@knu.ac.kr; ⓘ
Choi, Yundo
(Choi, Y) ⓘ 		Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu, South Korea ⓘ
ⓘ
ⓘ 		FODAS: A Novel Reinforcement Learning Approach for Efficient Task Scheduling in Fog Computing Network ⓘ ⓘ ⓘ ndganesan@gmail.com;ydchoi97@knu.ac.kr;kyong.kim@knu.ac.kr; ⓘ
Choi, Yunja
(Choi, Y) ⓘ 		교신저자 Kyungpook Natl Univ, Sch Comp Sci & Engr, Daegu, South Korea ⓘ
ⓘ
ⓘ 		Non-Functional Requirements Discovery and Quality Assurance using Goal Model for Earthquake Warning System in Operation ⓘ ⓘ ⓘ youngsulshin@gmail.com;leesw@ajou.ac.kr;yuchoi76@knu.ac.kr; ⓘ
Chun, Yoon Hong
(Chun, YH) ⓘ 		Catholic Univ Korea, Coll Med, Dept Pediat, Seoul, South Korea ⓘ
ⓘ
ⓘ 		Allergic rhinitis and hygiene hypothesis ⓘ ⓘ ⓘ pymcko@gmail.com; ⓘ
Chung, Goo-Bong
(Chung, GB) ⓘ 		Korea Inst Robot & Technol Convergence, Pohang 37666, South Korea ⓘ
ⓘ
ⓘ 		Development of In-Pipe Inspection Robot for Large-Diameter Water Pipe ⓘ ⓘ ⓘ hjchung@kiro.re.kr; ⓘ
Colaco, Savina Jassica
(Colaco, SJ) ⓘ 		제1저자 Kyungpook Natl Univ, Ctr ICT & Automot Convergence, Daegu, South Korea ⓘ
ⓘ
ⓘ 		Scalable Emotion Recognition Model with Context Information for Driver Monitoring System ⓘ ⓘ ⓘ savinacolaco@knu.ac.kr;dshan@knu.ac.kr; ⓘ
Cui, Shuyu
(Cui, S) ⓘ 		Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea ⓘ
ⓘ
ⓘ 		An Indoor Positioning Method Using High Probability RSSI ⓘ ⓘ ⓘ 2023000464@knu.ac.kr;jgpark@knu.ac.kr;cuishuyu@knu.ac.kr;dong116745@knu.ac.kr;rana.lila98@knu.ac.kr;junkyu891015@gmail.com; ⓘ
Dasari, Kasi Viswanath
(Dasari, KV) ⓘ 		제1저자 Univ Hyderabad, Sch Comp & Informat Sci, Hyderabad 500046, Telangana, India ⓘ O-5251-2016
viswanath, kasi ⓘ
ⓘ 		A General Variable Neighborhood Search Approach for the Clustered Traveling Salesman Problem with d-Relaxed Priority Rule ⓘ ⓘ ⓘ dasarivisu@gmail.com;alokcs@uohyd.ernet.in;mallipeddi.ram@gmail.com; ⓘ
Dayton, Paul A.
(Dayton, PA) ⓘ 		Univ North Carolina Chapel Hill, Joint Dept Biomed Engn, Chapel Hill, NC USA
NC State Univ, Chapel Hill, NC USA ⓘ
ⓘ
ⓘ 		Acoustic Metastructure-Lensed Multi-Focal Sonicator Designs for High-Throughput Therapeutic Ultrasound Testing In Vitro ⓘ ⓘ ⓘ jinwookkim@knu.ac.kr;sunny.kasoji@trianglebio.com;padayton@email.unc.edu; ⓘ
Do, Eun-Ju
(Do, EJ) ⓘ 		Kyungpook Natl Univ, Daegu, South Korea
Kyungpook Natl Univ, Dept Elect Engn, Daegu, South Korea ⓘ
ⓘ
ⓘ 		A Data-Gathering Underwater Medium Access Control Scheme Using Carrier Sensing Associated Machine Learning
A Sink-Triggered Data Gathering Protocol in Underwater Sensor Network ⓘ 		ⓘ ⓘ 2048jw@knu.ac.kr;sarah7993@knu.ac.kr;ij020226@naver.com;hscho@ee.knu.ac.kr; ⓘ
Dong, Jiabin
(Dong, J) ⓘ 		제1저자 Kyungpook Natl Univ, Elect & Elect Engn, Daegu, South Korea
Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea ⓘ
ⓘ
ⓘ 		Indoor Positioning Using Wi-Fi RTT based on Stacked Ensemble Model
An Indoor Positioning Method Using High Probability RSSI ⓘ 		ⓘ ⓘ dong116745@knu.ac.kr;rana.lila98@knu.ac.kr;2023000464@knu.ac.kr;junkyu891015@gmail.com;jgpark@knu.ac.kr;
2023000464@knu.ac.kr;jgpark@knu.ac.kr;cuishuyu@knu.ac.kr;dong116745@knu.ac.kr;rana.lila98@knu.ac.kr;junkyu891015@gmail.com; ⓘ
Fakhry, Ahmed
(Fakhry, A) ⓘ 		제1저자 교신저자 Kyungpook Natl Univ, Daegu, South Korea ⓘ KSL-9541-2024
Emad El-Din, Ahmed ⓘ
ⓘ 		Enhancing Few-Shot Video Anomaly Detection with Key-Frame Selection and Relational Cross Transformers ⓘ ⓘ ⓘ ahmedfakhry@knu.ac.kr;jongtaeklee@knu.ac.kr; ⓘ
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