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    • UNIST Secures KRW 11 Billion in Research Funding for ‘AI Star Fellowship’ Project 7 days ago
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    • UNIST Secures KRW 11 Billion in Research Funding for ‘AI Star Fellowship’ Project 7 days ago
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Home Jaejun Yoo

Revolutionary AI Achieves Sharp, Accurate MRI Reconstruction for Cardiac and Blood Flow Imaging

Professor Jaejun Yoo presented a novel AI model for dynamic MRI reconstruction, which enhances image quality and accuracy while significantly reducing processing time.

Their research was selected for presentation at MICCAI 2025, a premier international conference in medical AI.

Revolutionary AI Achieves Sharp, Accurate MRI Reconstruction for Cardiac and Blood Flow Imaging

Abstract Dynamic MRI reconstruction, one of inverse problems, has seen a surge by the use of deep learning techniques. Especially, the practical difficulty of obtaining ground truth data has led to the emergence of unsupervised learning app... Read More

Sep 16, 2025 By JooHyeon Heo Research
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UNIST Unveils Cutting-Edge AI Model to Transform Blurry, Choppy Videos into Clear, Seamless Footage

Their findings have been accepted for presentation at the 2025 Conference on Computer Vision and Pattern Recognition (CVPR).

UNIST Unveils Cutting-Edge AI Model to Transform Blurry, Choppy Videos into Clear, Seamless Footage

Abstract While prior methods in Continuous Spatial-Temporal Video Super-Resolution (C-STVSR) employ Implicit Neural Representation (INR) for continuous encoding, they often struggle to capture the complexity of video data, relying on simple... Read More

Jun 27, 2025 By JooHyeon Heo Research
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Lightweight AI Model Developed to Facilitate High-Quality Image Generation Without Direct Transmission of Sensitive Data

Their findings have been presented at the CVPR 2025, which will take place in Singapore from April 24 to 28, 2025.

Lightweight AI Model Developed to Facilitate High-Quality Image Generation Without Direct Transmission of Sensitive Data

Abstract Despite recent advancements in federated learning (FL), the integration of generative models into FL has been limited due to challenges such as high communication costs and unstable training in heterogeneous data environments. To a... Read More

Apr 14, 2025 By JooHyeon Heo Research
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