F. Yıldırım

A computational framework for post-acquisition stability assessment in scanning tunneling microscopy

The proposed approach combines deterministic computer vision-based analyses with modern deep learning components in a hybrid workflow, producing pixel-level drift metrics together with local and surface-level image-similarity indicators based on the structural similarity index measure and normalized cross-correlation.