1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 1 cited
Few-shot Fine-tuning is All You Need for Source-free Domain Adaptation
Suho Lee, Seungwon Seo, Jihyo Kim +2
Recently, source-free unsupervised domain adaptation (SFUDA) has emerged as a more practical and feasible approach compared to unsupervised domain adaptation (UDA) which assumes th…
cs.CV2023
Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions
Jihyo Kim, Jeonghyeon Kim, Sangheum Hwang
Active learning aims to identify the most informative data from an unlabeled data pool that enables a model to reach the desired accuracy rapidly. This benefits especially deep neu…