UniMR: A Plug-and-Play Framework of Automated Molecular Recognition for Scanning Tunneling Microscopy.

ABSTRACT: Scanning Tunneling Microscopy (STM) has become an indispensable tool for molecular surface chemistry, where recognizing molecules in STM images is a fundamental task. Human annotation requires a great deal of domain knowledge and is laborious, while current automated methods usually require training and focus on particular molecular systems. In this work, a training-free universal molecular recognizer (UniMR) is developed that is widely applicable to various molecular systems and is tolerant of low-resolution images. UniMR integrates off-the-shelf computer vision tools with a feature adaptive selection module. First, input images are normalized to ensure consistent molecular brightness and orientation. To address the varying complexity of molecular differentiation across different systems,

SUBMITTER: Cao Z 

PROVIDER: S-EPMC12931239 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature