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유재준
Yoo, Jaejun

유재준

인공지능대학원

  • Lab. of Advanced Imaging Technology
  • Website
Research Interests
AI;Computer Vision;Medical Image Processing;Machine Learning;인공지능;컴퓨터 비전;의료영상처리;머신러닝
Lab Description
Our main research area lies at the intersection of computer vision, machine learning, and inverse problems, including natural image recovery and medical imaging. We have a strong interest in generative models, representation learning, and the use of signal processing theories for image processing. Our goal is to build strong and intelligent signal processing models, capable of recreating the world we perceive. We aim to establish a bridge between signal processing and deep learning, taking the best of both worlds. We study deep learning models that learn structural priors by synthesizing and modeling millions of images and videos. Along the way, the learned models provide insights to seek mathematical elegance and a clear understanding of our world, which in turn encourages us to find better models to analyze signals in nature.
Researcher ID Research Gate ORCiD Scopus Google Scholar
Previous
Deep learning enhances reliability of dynamic contrast-enhanced MRI in diffuse gliomas: bypassing post-processing and providing uncertainty maps File

Lyoo, Young Wook , Lee, Haneol , Lee, Junhyeok , Park, Jung Hyun , Hwang, Inpyeong , Chung, Jin Wook , Choi, Seung Hong , Yoo, Jaejun , Choi, Kyu Sung

Article Issue Date2025-10 View155
Multimodal Semantic Segmentation in Yangtze River Economic Belt: Outcome of the 2024 IEEE WHISPERS MMSeg-YREB Challenge File

Li, Jiepan , Huang, He , Xia, Yu , Xu, Xian , Wu, Yingxin , Guo, Qi , Liu, Yinhe , Zhong, Yanfei , Min, Jeongho , Son, Sungbin , et al

Article Issue Date2025-08 View56
Deep learning-driven automated mitochondrial segmentation for analysis of complex transmission electron microscopy images File

Jang, Chan , Lee, Hojun , Yoo, Jaejun , Yoon, Haejin

Article Issue Date2025-05 View93
Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch File

Kim, Pum Jun , Kim, Dongyoung , Lee, Joonwon , Kim, Hyung Chan , Seo, Jung Hwa , Lee, Suk Yoon , Kwon, Doo Hyuk , Park, Hyungjong , Yoo, Jaejun , Park, Seongho

Article Issue Date2025-02 View129
Style harmonization of panoramic radiography using deep learning File

Kim, Hak-Sun , Seol, Jaejung , Lee, Ji-Yun , Han, Sang-Sun , Yoo, Jaejun , Lee, Chena

Article Issue Date2025-01 View127
Motion-based Frame Sampling for Natural Language-based Vehicle Retrieval File

Kim, Dongyoung , Lee, Kyoungoh , Jang, In-su , Kim, Kwang-Ju , Kim, Pyong-Kun , Yoo, Jaejun

Article Issue Date2024-11 View108
Universal Dehazing via Haze Style Transfer File

Park, Eunpil , Yoo, Jaejun , Sim, Jae-Young

Article Issue Date2024-09 View164
Data Augmentation for Low-Level Vision: CutBlur and Mixture-of-Augmentation File

Ahn, Namhyuk , Yoo, Jaejun , Sohn, Kyung-Ah

Article Issue Date2024-06 View169
Bridging the Domain Gap: A Simple Domain Matching Method for Reference-Based Image Super-Resolution in Remote Sensing File

Min, Jeongho , Lee, Yejun , Kim, Dongyoung , Yoo, Jaejun

Article Issue Date2024-01 View121
Dynamic Fourier ptychography with deep spatiotemporal priors File File

Bohra, Pakshal , Pham, Thanh-an , Long, Yuxuan , Yoo, Jaejun , Unser, Michael

Article Issue Date2023-06 View131
GAN 기반 의료영상 생성 모델에 대한 품질 및 다양성 평가 및 분석 File

장유진 , 유재준 , 홍헬렌

Article Issue Date2022-07 View99
Time-Dependent Deep Image Prior for Dynamic MRI File

Yoo, Jaejun , Jin, Kyong Hwan , Gupta, Harshit , Yerly, Jerome , Stuber, Matthias , Unser, Michael

Article Issue Date2021-12 View118
Deep Learning Diffuse Optical Tomography File

Yoo, Jaejun , Sabir, Sohail , Heo, Duchang , Kim, Kee Hyun , Wahab, Abdul , Choi, Yoonseok , Lee, Seul-, I , Chae, Eun Young , Kim, Hak Hee , Bae, Young Min , et al

Article Issue Date2020-04 View107
A MATHEMATICAL FRAMEWORK FOR DEEP LEARNING IN ELASTIC SOURCE IMAGING File

Yoo, Jaejun , Wahab, Abdul , Ye, Jong Chul

Article Issue Date2018-10 View111
Deep learning with domain adaptation for accelerated projection-reconstruction MR File

Han, Yoseob , Yoo, Jaejun , Kim, Hak Hee , Shin, Hee Jung , Sung, Kyunghyun , Ye, Jong Chul

Article Issue Date2018-09 View89
Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks File

Lee, Dongwook , Yoo, Jaejun , Tak, Sungho , Ye, Jong Chul

Article Issue Date2018-09 View123
Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network File

Kang, Eunhee , Chang, Won , Yoo, Jaejun , Ye, Jong Chul

Article Issue Date2018-06 View127
Alteration in the Local and Global Functional Connectivity of Resting State Networks in Parkinson's Disease File

Ghahremani, Maryam , Yoo, Jaejun , Chung, Sun Ju , Yoo, Kwangsun , Ye, Jong C. , Jeong, Yong

Article Issue Date2018-01 View123
A Joint Sparse Recovery Framework for Accurate Reconstruction of Inclusions in Elastic Media File

Yoo, Jaejun , Jung, Younghoon , Lim, Mikyoung , Ye, Jong Chul , Wahab, Abdul

Article Issue Date2017-08 View169
Topological persistence vineyard for dynamic functional brain connectivity during resting and gaming stages File

Yoo, Jaejun , Kim, Eun Young , Ahn, Yong Min , Ye, Jong Chul

Article Issue Date2016-07 View93
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