Defect detection and classification on imec iN5 node BEoL test vehicle with MultiSEM Interuniversity Microelectronics Centre
We present an automated application for defect detection and classification from ZEISS MultiSEM (R) images, based on Machine Learning ( ML) technology. We acquire MultiSEM images of a semiconductor wafer suited for process window characterization at the imec iN5 logic node and use a dedicated application to train ML models for defect detection and classification. We show the user flow for training and execution, and the resulting capture and ...