AIBullisharXiv – CS AI · 18h ago6/10
🧠
Context-Aware Deep Learning for Defect Classification in Atomic-Resolution STEM
Researchers developed a context-aware deep learning framework that integrates image contrast with metadata (composition, beam energy, detector geometry) to classify defects in electron microscopy with 98% accuracy on simulations. The approach demonstrates that incorporating physical and experimental context transforms defect classification from an ambiguous image-only task into a well-posed, scientifically grounded problem.