Kanggeun Lee
Kanggeun Lee
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Contact
Github: github.com/leekanggeun
Linkedin: www.linkedin.com/in/kingcarrot
Research Interests
Machine Learning (Self-supervised-, unsupervised-, weakly supervised-, semi-supervised learning)
Image Processing (Image denoising, super-resolution, reconstruction, segmentation, classification, abnormal detection, etc.)
Data Analysis (Feature selection, feature extraction, etc.)
Education & Experience
Korea University (KU)
Research Professor (Mar. 2022 - Present)
Ulsan National Institute of Science and Technology (UNIST)
M.S. and Ph.D. in Computer Science and Engineering (Mar. 2017 - Feb. 2022)
B.S. in Computer Science and Engineering (Mar. 2012 - Feb. 2017)
Projects
Challenge (Organizer)
PAIP2021: Perineural Invasion in Multiple Organ Cancer (https://paip2021.grand-challenge.org/)
PAIP2020: MSI Prediction in Colorectal Cancer (https://paip2020.grand-challenge.org/Home/)
PAIP2019: Liver Cancer Segmentation (http://www.wisepaip.org/paip)
Research
Machine learning framework based software development for genome analysis (Nov. 2016 - Oct. 2022)
Development of machine learning frameworks and analysis tools for histopathology Whole Slide image (WSI) (Apr. 2018 - Feb. 2023)
Development of AI-AR-based real-time signal processing, image analysis, and visualization techniques for a smart microscope. (Jun. 2019 - Feb. 2023)
Skills
Programming
Python, C/C++, Matlab
Framework & Library
Tensorflow and Pytorch.
Language
Korean, English
Publications
I2V: Towards Texture-Aware Self-Supervised Blind Denoising using Self-Residual Learning for Real-World Images
I2V: Towards Texture-Aware Self-Supervised Blind Denoising using Self-Residual Learning for Real-World Images
Kanggeun Lee, Kyungryun Lee, and Won-Ki Jeong
Under Review
Kanggeun Lee, Jin-Ho Jang, Dongbin Cho, Jiwon Seo, Semin Lee, and Won-Ki Jeong
Briefings in Bioinformatics
Impact Factor: 13.994
JCR Ranking: 1.8% (Mathematical & Computational Biology 1 out of 57)
Kangguen Lee and Won-Ki Jeong
MDPI Sensors 22.11 (2022): 4255.
Impact Factor: 3.735 (5-Year IF)
Kanggeun Lee and Won-Ki Jeong
IEEE Transactions on Medical Imaging 40.11 (2021): 3238-3248.
Impact Factor: 11.037
JCR Ranking: 2.9% (4/134)
It was presented as a special session in Korean Society of Artificial Intelligence in Medicine (KoSAIM 2021).
Kanggeun Lee, Hyoung-oh Jeong, Semin Lee, and Won-Ki Jeong
Scientific Reports 9.1 (2019): 1-9.
Impact Factor: 5.133 (5-Year IF)
Kanggeun Lee and Won-Ki Jeong
Journal of the Korea Computer Graphics Society 27 (5), 45-54
Korea Citation Index (KCI)
Yoo Jung Kim, Hyungjoon Jang, Kyoungbun Lee, Seongkeun Park, Sung-Gyu Min, Choyeon Hong, Jeong Hwan Park, Kanggeun Lee et al.
Medical Image Analysis 67 (2021): 101854
Impact Factor: 13.828
JCR Ranking: 1.4% (2/134)
Chanmin Park, Kanggeun Lee, Su Yeon Kim, Fatma Sema Canbakis Cecen, Seok-Kyu Kwon, and Won-Ki Jeong
IEEE International Symposium on Biomedical Imaging (ISBI) 2021
Jing Wei Tan, Kanggeun Lee, Kyoungbun Lee, Won-Ki Jeong
IEEE International Symposium on Biomedical Imaging (ISBI) 2021 (Oral)
Hyun-Jic Oh, Kangguen Lee, Won-Ki Jeong
IEEE International Symposium on Biomedical Imaging (ISBI) 2022
Undersampled MRI Reconstruction using Switchable Interdependent Self-Cooperative Learning without Paired Training Data
Undersampled MRI Reconstruction using Switchable Interdependent Self-Cooperative Learning without Paired Training Data
Suemin Jeon, Kangguen Lee, Won-Ki Jeong
IEEE International Symposium on Biomedical Imaging (ISBI) 2023
Tran Minh Quan, David Grant Colburn Hildebrand, Kanggeun Lee, Logan A Thomas, Aaron T Kuan, Wei-Chung Allen Lee, Won-Ki Jeong
IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) 2019
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