1 citations · 1 across the 4 of their papers we have counts for
4 papers
When Test-Time Adaptation Meets Self-Supervised Models
Jisu Han, Jihee Park, Dongyoon Han +1
Training on test-time data enables deep learning models to adapt to dynamic environmental changes, enhancing their practical applicability. Online adaptation from source to target…
Ranked Entropy Minimization for Continual Test-Time Adaptation
Jisu Han, Jaemin Na, Wonjun Hwang
Test-time adaptation aims to adapt to realistic environments in an online manner by learning during test time. Entropy minimization has emerged as a principal strategy for test-tim…
Semantic Prompting with Image-Token for Continual Learning
Jisu Han, Jaemin Na, Wonjun Hwang
Continual learning aims to refine model parameters for new tasks while retaining knowledge from previous tasks. Recently, prompt-based learning has emerged to leverage pre-trained…
SRIL: Selective Regularization for Class-Incremental Learning
Jisu Han, Jaemin Na, Wonjun Hwang
Human intelligence gradually accepts new information and accumulates knowledge throughout the lifespan. However, deep learning models suffer from a catastrophic forgetting phenomen…