SAM-I-Am: Semantic Boosting for Zero-shot Atomic-Scale Electron Micrograph Segmentation

Semantic boosting can enable rapid adaptation of the Segment Anything Model (SAM) to perform zero-shot microstructure segmentation of transmission electron microscopy (TEM) images, overcoming the limitations of the vanilla SAM pipeline.