Signal Learning Lab
Signal Learning Lab
Korea University · Electrical Engineering
Professor
Prof. 황원준
Professor's page · publicationsAbout
황원준 교수 연구실(Signal Learning Lab)은 고려대 전기전자공학부 소속으로, 패턴 인식과 딥러닝을 연구한다. 파운데이션 모델 기반의 효율적 딥러닝 기법에 중점을 두며 test-time adaptation, semantic segmentation, continual learning, domain adaptation, knowledge distillation 등을 다룬다.
Research keywords
Recent papers
- Adaptive multi-bit progressive quantization for stable training of binary neural networksMultimedia Tools and Applications · Sep 7
- Collaborative adaptation without forgetting in source-free domain adaptationPattern Recognition · Jul 30
From OpenAlex · papers whose author affiliation matches this university
Selected publications
- Ranked Entropy Minimization for Continual Test-Time AdaptationInternational Conference on Machine Learning (ICML) · 2025
- Semantic Prompting with Image Token for Continual LearningIEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · 2025
- D3T: Distinctive Dual-Domain Teacher Zigzagging Across RGB-Thermal Gap for Domain-Adaptive Object DetectionIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2024
- Switching Temporary Teachers for Semi-supervised Semantic SegmentationAdvances in Neural Information Processing Systems (NeurIPS) · 2023
- itKD: Interchange Transfer-based Knowledge Distillation for 3D Object DetectionIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2023
- Contrastive Vicinal Space for Unsupervised Domain AdaptationEuropean Conference on Computer Vision (ECCV) · 2022
Labs doing related research
Labs that recently published on topics this lab's recent papers share
Shared topic: Domain Adaptation and Few-Shot Learning
Kim Junmo Lab
KAIST · Electrical Engineering
MLLMCLIP: Feature-Level Distillation of MLLM for Robust Vision-Language RepresentationsNewPreprintarXiv (Cornell University) · Aug 26Ubiquitous AI Lab (UAILab)
Ulsan National Institute of Science and Technology (UNIST) · Computer Science and Engineering
ACE: Adapter Consolidation across Experts for Parameter-Efficient Fine-Tuning of MoE LLMsPreprintarXiv (Cornell University) · Sep 5Visual Intelligence Lab
KAIST · Mechanical Engineering
Preference-Guided Adaptation for Open-Vocabulary Semantic Segmentation via Prompt DisagreementPreprintarXiv (Cornell University) · Sep 28
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