5 papers
Preserving Pre-trained Representation Space: On Effectiveness of Prefix-tuning for Large Multi-modal Models
Donghoon Kim, Gusang Lee, Kyuhong Shim +1
Recently, we have observed that Large Multi-modal Models (LMMs) are revolutionizing the way machines interact with the world, unlocking new possibilities across various multi-modal…
Depth-Relative Self Attention for Monocular Depth Estimation
Kyuhong Shim, Jiyoung Kim, Gusang Lee +1
Monocular depth estimation is very challenging because clues to the exact depth are incomplete in a single RGB image. To overcome the limitation, deep neural networks rely on vario…
Feasibility Study of Multi-Site Split Learning for Privacy-Preserving Medical Systems under Data Imbalance Constraints in COVID-19, X-Ray, and Cholesterol Dataset
Yoo Jeong Ha, Gusang Lee, Minjae Yoo +3
It seems as though progressively more people are in the race to upload content, data, and information online; and hospitals haven't neglected this trend either. Hospitals are now a…
Spatio-Temporal Split Learning for Privacy-Preserving Medical Platforms: Case Studies with COVID-19 CT, X-Ray, and Cholesterol Data
Yoo Jeong Ha, Minjae Yoo, Gusang Lee +4
Machine learning requires a large volume of sample data, especially when it is used in high-accuracy medical applications. However, patient records are one of the most sensitive pr…
Visualization of Deep Reinforcement Autonomous Aerial Mobility Learning Simulations
Gusang Lee, Won Joon Yun, Soyi Jung +2
This demo abstract presents the visualization of deep reinforcement learning (DRL)-based autonomous aerial mobility simulations. In order to implement the software, Unity-RL is use…