Sunghyun Ahn

최신

• AMoE-BTS: An Adaptive Mixture of Experts for Clinical Decision Support in Multimodal Brain Tumor Segmentation
• GranQ: Efficient Channel-wise Quantization via Vectorized Pre-Scaling for Zero-Shot QAT
• AnyAnomaly: Zero-shot Customizable Video Anomaly Detection with LVLM
• Unified Video Anomaly Detection Model for Detecting Different Anomaly Types
• MDVAD: Multimodal Diffusion for Video Anomaly Detection
• Advanced Knowledge Transfer: Refined Feature Distillation for Zero-Shot Quantization in Edge Computing
• VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection
• Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer
• Dual Stream Fusion U-Net Transformers for 3D Medical Image Segmentation