AI-Vision Lab5
Our lab aims to address computer vision challenges across diverse domains—including natural images, medical imaging, and industrial scenes—by leveraging state-of-the-art AI technologies. We are dedicated to designing novel models, extracting meaningful information from data, and conducting in-depth analysis to solve real-world problems. Through these efforts, we strive to build intelligent systems that can robustly interpret complex visual environments and contribute to both scientific advancement and societal impact.
Principal Investigator : Kim, Soopil
AI-Vision Lab Homepage
Principal Investigator : Kim, Soopil
AI-Vision Lab Homepage
Date issued
- 2025 4
Co-Author(s)
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Recent Submissions
- Logical Anomaly Detection with Text-based Logic via Component-Aware Contrastive Language-Image Training
- MOSInversion: Knowledge distillation-based incremental learning in organ segmentation using DeepInversion
- 산업데이터 이상감지 전처리 요소 기술
- Revisiting Masked Image Modeling with Standardized Color Space for Domain Generalized Fundus Photography Classification
- MC-NuSeg: Multi-Contour Aware Nuclei Instance Segmentation with Segment Anything Model
