Mining Lithography Hotspots from Massive SEM Images Using Machine Learning Model

An effect method based on machine learning is developed for hotspots mining in lithography. A series of models are trained independently and combined to achieve high accuracy. Innovatively, contour information is firstly adopted to assist the hotspot detection, which eases the very challenging task of detection for topology aberration caused by complicated process effects. More importantly, the proposed method based on new methodology provides high efficiency which is competent for high volume manufacturing.