5 papers
SleepMaMi: A Universal Sleep Foundation Model for Integrating Macro- and Micro-structures
Keondo Park, Younghoon Na, Yourim Choi +3
While the shift toward unified foundation models has revolutionized many deep learning domains, sleep medicine remains largely restricted to task-specific models that focus on loca…
T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation
Dongik Park, Hyunwoo Ryu, Suahn Bae +2
Imputing missing values in multivariate time series remains challenging, especially under diverse missing patterns and heavy missingness. Existing methods suffer from suboptimal pe…
AI Should Sense Better, Not Just Scale Bigger: Adaptive Sensing as a Paradigm Shift
Eunsu Baek, Keondo Park, Jeonggil Ko +3
Current AI advances largely rely on scaling neural models and expanding training datasets to achieve generalization and robustness. Despite notable successes, this paradigm incurs…
PointSplit: Towards On-device 3D Object Detection with Heterogeneous Low-power Accelerators
Keondo Park, You Rim Choi, Inhoe Lee +1
Running deep learning models on resource-constrained edge devices has drawn significant attention due to its fast response, privacy preservation, and robust operation regardless of…
Unexplored Faces of Robustness and Out-of-Distribution: Covariate Shifts in Environment and Sensor Domains
Eunsu Baek, Keondo Park, Jiyoon Kim +1
Computer vision applications predict on digital images acquired by a camera from physical scenes through light. However, conventional robustness benchmarks rely on perturbations in…