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Deokwoo Lee - PI
Deokwoo Lee - PI
Associate Professor, Department of Computer Engineering, Keimyung University, Daegu, Republic of Korea
Associate Professor, Department of Computer Engineering, Keimyung University, Daegu, Republic of Korea
- Phone : 053-580-5268
- Office : Engineering Bldg I - Room1323
Research Interests
Research Interests
- Signal Processing
- Image Processing
- Computer Vision
Biography : Deokwoo LEE is currently working at Keimyung University as an associate professor. He joined KMU in March 2018.He completed his undergraduate study in electrical engineering at Kyungpook National University in 2007, Daegu, Republic of Korea. He completed his mandatory military service in Korean Army from 2002 to 2004. He earned M.S and Ph.D degrees in electrical engineering at North Carolina Sate University, Raleigh, NC, USA in 2008 and 2012, respectively. He earned minor Ph.D degree in mathematics. He worked in VISSTA group at NCSU as a graduate research/teaching assistant under supervision by Dr. Hamid Krim who also guided master and doctoral research. During his graduate study, his research focused on determination of sampling criterion for multidimensional signals including 2D and 3D images. He also worked on computer vision, especially on 3D reconstruction, depth estimation using passive and active methods and camera calibration. After his doctoral course, he worked on medical image analysis as a postdoctoral research associate in Medical Imaging and Bioinformatics Lab at Washington University in St. Louis, St. Louis, MO, USA for a few months in 2013. He joined a Group of Mobile Camera Development at Samsung Electronics, Suwon, Republic of Korea in September 2013. He worked on developing SW algorithm for mobile camera. From September 2016 to February 2018, he worked at Youngsan University, Busan as an assistant professor. His current research covers theory and applications in computer vision, image and signal processing from mathematical and statistical perspectives.
Biography : Deokwoo LEE is currently working at Keimyung University as an associate professor. He joined KMU in March 2018.He completed his undergraduate study in electrical engineering at Kyungpook National University in 2007, Daegu, Republic of Korea. He completed his mandatory military service in Korean Army from 2002 to 2004. He earned M.S and Ph.D degrees in electrical engineering at North Carolina Sate University, Raleigh, NC, USA in 2008 and 2012, respectively. He earned minor Ph.D degree in mathematics. He worked in VISSTA group at NCSU as a graduate research/teaching assistant under supervision by Dr. Hamid Krim who also guided master and doctoral research. During his graduate study, his research focused on determination of sampling criterion for multidimensional signals including 2D and 3D images. He also worked on computer vision, especially on 3D reconstruction, depth estimation using passive and active methods and camera calibration. After his doctoral course, he worked on medical image analysis as a postdoctoral research associate in Medical Imaging and Bioinformatics Lab at Washington University in St. Louis, St. Louis, MO, USA for a few months in 2013. He joined a Group of Mobile Camera Development at Samsung Electronics, Suwon, Republic of Korea in September 2013. He worked on developing SW algorithm for mobile camera. From September 2016 to February 2018, he worked at Youngsan University, Busan as an assistant professor. His current research covers theory and applications in computer vision, image and signal processing from mathematical and statistical perspectives.
Thesis / Dissertation Supervision
Thesis / Dissertation Supervision
이호정, 딥러닝 활용 표정 인식 기반의 과정 중심 평가 방법에 관한 연구, 교육대학원 전산교육전공 석사, 2020년 2월
김지수, 심층신경망을 이용한 시각집중 기반의 행동인식, 일반대학원 컴퓨터공학과 석사, 2021년 2월
박철형, 특징 시각화와 합성곱 신경망 기반의 호흡 분류, 일반대학원 컴퓨터공학과 석사, 2021년 8월
김지은, 변형가능한 합성곱 기반의 시각언어 모델, 일반대학원 컴퓨터공학과 석사, 2023년 2월
Boulaouane Youssef, Image Classification Based on Convolutional Neural Network using Knowledge Distillation and Efficient Channel Attention, 일반대학원 컴퓨터공학과 석사 2023년 8월
김주오, 심층학습 기반 초광대역 레이더 센서를 활용한 비정상 호흡신호 감지, 일반대학원 컴퓨터공학과 석사 2025년 8월
장진원, Domain Adaptation Network Model based Object Detection with Optimization using Knowledge Distillation, 일반대학원 컴퓨터공학과 석사 2025년 8월
Teaching
Teaching
Spring/2025
Spring/2025
Operating Systems
Software Engineering
Vehicular Vision Systems
Fall/2025
Fall/2025
Concepts of Programming Languages
Mathematics for AI
Information Theory(Graduate)
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