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2020 – today
- 2024
[j8]Daeahn Cho, Myeong-Sang Yu, Jeongyoon Shin, Jingyu Lee, Yubin Kim, Hoon-Chul Kang, Se Hee Kim, Dokyun Na
:
A computational clinical decision-supporting system to suggest effective anti-epileptic drugs for pediatric epilepsy patients based on deep learning models using patient's medical history. BMC Medical Informatics Decis. Mak. 24-S(2): 149 (2024)- [c4]Jingyu Lee, Hyunsoo Kim, Minjae Kim, Byung-Gon Chun, Youngki Lee:
Maestro: The Analysis-Simulation Integrated Framework for Mixed Reality. MobiSys 2024: 99-112 - [c3]Jingyu Lee, Hyunsoo Kim, Minjae Kim, Byung-Gon Chun, Youngki Lee:
Poster: Maestro: The Analysis-Simulation Integrated Framework for Mixed Reality. MobiSys 2024: 670-671 - 2023
- [j7]Bilal Shaker, Jingyu Lee, Yunhyeok Lee, Myeong-Sang Yu, Hyang-Mi Lee, Eunee Lee, Hoon-Chul Kang, Kwang-Seok Oh, Hyung Wook Kim, Dokyun Na:
A machine learning-based quantitative model (LogBB_Pred) to predict the blood-brain barrier permeability (logBB value) of drug compounds. Bioinform. 39(10) (2023) - 2022
- [c2]Joo Seong Jeong, Jingyu Lee, Donghyun Kim, Changmin Jeon, Changjin Jeong, Youngki Lee, Byung-Gon Chun:
Band: coordinated multi-DNN inference on heterogeneous mobile processors. MobiSys 2022: 235-247 - 2021
- [j6]Minyoung Chung, Jingyu Lee, Sanguk Park, Chae-Eun Lee, Jeongjin Lee, Yeong-Gil Shin:
Liver segmentation in abdominal CT images via auto-context neural network and self-supervised contour attention. Artif. Intell. Medicine 113: 102023 (2021) - [j5]Bilal Shaker, Sajjad Ahmad, Jingyu Lee, Chanjin Jung, Dokyun Na:
In silico methods and tools for drug discovery. Comput. Biol. Medicine 137: 104851 (2021) - [c1]Jingyu Lee, Yunxin Liu, Youngki Lee:
ParallelFusion: Towards Maximum Utilization of Mobile GPU for DNN Inference. EMDL@MobiSys 2021: 25-30 - 2020
- [j4]Myeong-Sang Yu, Jingyu Lee, Yongmin Lee, Dokyun Na:
2-D chemical structure image-based in silico model to predict agonist activity for androgen receptor. BMC Bioinform. 21-S(5): 245 (2020) - [j3]Minyoung Chung, Minkyung Lee, Jioh Hong, Sanguk Park, Jusang Lee, Jingyu Lee, Il-Hyung Yang, Jeongjin Lee, Yeong-Gil Shin:
Pose-aware instance segmentation framework from cone beam CT images for tooth segmentation. Comput. Biol. Medicine 120: 103720 (2020) - [j2]Minyoung Chung, Jingyu Lee, Minkyung Lee, Jeongjin Lee, Yeong-Gil Shin:
Deeply self-supervised contour embedded neural network applied to liver segmentation. Comput. Methods Programs Biomed. 192: 105447 (2020) - [j1]Minyoung Chung, Jingyu Lee, Wisoo Song, Youngchan Song, Il-Hyung Yang, Jeongjin Lee, Yeong-Gil Shin:
Automatic Registration Between Dental Cone-Beam CT and Scanned Surface via Deep Pose Regression Neural Networks and Clustered Similarities. IEEE Trans. Medical Imaging 39(12): 3900-3909 (2020) - [i4]Minyoung Chung, Minkyung Lee, Jioh Hong, Sanguk Park, Jusang Lee, Jingyu Lee, Jeongjin Lee, Yeong-Gil Shin:
Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation. CoRR abs/2002.02143 (2020) - [i3]Minyoung Chung, Jingyu Lee, Jeongjin Lee, Yeong-Gil Shin:
Liver Segmentation in Abdominal CT Images via Auto-Context Neural Network and Self-Supervised Contour Attention. CoRR abs/2002.05895 (2020)
2010 – 2019
- 2019
- [i2]Minyoung Chung, Jingyu Lee, Wisoo Song, Youngchan Song, Il-Hyung Yang, Jeongjin Lee, Yeong-Gil Shin:
Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities. CoRR abs/1907.12250 (2019) - 2018
- [i1]Minyoung Chung, Jingyu Lee, Minkyung Lee, Jeongjin Lee, Yeong-Gil Shin:
Deeply Self-Supervising Edge-to-Contour Neural Network Applied to Liver Segmentation. CoRR abs/1808.00739 (2018)
Coauthor Index
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