Sunghyun Ahn
Scholar

Sunghyun Ahn

Google Scholar ID: mKchEwoAAAAJ
Yonsei University
Multimodal Deep LearningComputer VisionVideo UnderstandingAnomaly Detection
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
33
 
H-index
3
 
i10-index
1
 
Publications
13
 
Co-authors
0
 
Contact
Emailcse@shacoding.comGitHubOpen ↗LinkedInOpen ↗
Publications
3 items
GranQ: Granular Zero-Shot Quantization with Unified Layer-Channel Awareness
2025
Cited
0
AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLM
2025
Cited
0
Advanced Knowledge Transfer: Refined Feature Distillation for Zero-Shot Quantization in Edge Computing
2024
Cited
0
Resume
Academic Achievements
  • - AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLM (WACV 2026)
  • - VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection (ACCV 2024)
  • - Making Anomalies More Anomalous: Video Anomaly Detection Using a Novel Generator and Destroyer (IEEE Access, 2024)
  • - Dual Stream Fusion U-Net Transformers for 3D Medical Image Segmentation (BigComp 2024)
Research Experience
  • Insufficient information
Education
  • Insufficient information
Background
  • Research Interests: Computer Science, Data Science, Coding
  • Fields of Expertise: Architecture, Algorithms, Data Structures, Databases & Files, Operating Systems, Networks, Data Analysis, Data Mining, Machine Learning, Computer Vision, AI Paper Review, Statistics
  • Introduction: A researcher who likes coding and AI
Miscellany
  • Personal Interests: Coding and AI