3 citations · 6 across the 7 of their papers we have counts for
4 papers · 1 filter
Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation
Jeongin Kim, Wonho Bae, YouLee Han +4
Semantic segmentation demands dense pixel-level annotations, which can be prohibitively expensive - especially under extremely constrained labeling budgets. In this paper, we addre…
SlumpGuard: An AI-Powered Real-Time System for Automated Concrete Slump Prediction via Video Analysis
Youngmin Kim, Giyeong Oh, Kwangsoo Youm +1
Concrete workability is essential for construction quality, with the slump test being the most widely used on-site method for its assessment. However, traditional slump testing is…
Revisiting Residual Connections: Orthogonal Updates for Stable and Efficient Deep Networks
Giyeong Oh, Woohyun Cho, Siyeol Kim +2
Residual connections are pivotal for deep neural networks, enabling greater depth by mitigating vanishing gradients. However, in standard residual updates, the module's output is d…
SEAL: Entangled White-box Watermarks on Low-Rank Adaptation
Giyeong Oh, Saejin Kim, Woohyun Cho +4
Recently, LoRA and its variants have become the de facto strategy for training and sharing task-specific versions of large pretrained models, thanks to their efficiency and simplic…