Applied Materials Israel Limited

Dror Alumot

Shaul Cohen

Shalom Elkayam

Anna Levant

Uri Hadar

Gilad Vered

Yarden Zohar

Elran Gamzo

Tamir Einy

There is provided an image generation system and method. The method comprises obtaining a runtime image of a semiconductor specimen with a low Signal-to-noise ratio (SNR), and processing the runtime image using a machine learning (ML) model to obtain an output image with a high SNR. The ML model is previously trained using a training set comprising a plurality of low SNR images associated with a high SNR image. The plurality of low SNR images correspond to a plurality of sequences of frames acquired in a plurality of runs of scanning a first site of the specimen. The high SNR image is generated based on the plurality of low SNR images. The training comprises, for each low SNR image: processing the low SNR image by the ML model to obtain predicted image data, and optimizing the ML model based on the predicted image data and the high SNR image.

Image denoising for examination of a semiconductor specimen

There is provided a system and method of examining a specimen comprising a first layer and a second layer. The method comprises obtaining a recipe including a template image for each reference polygon in a reference image and a template mask indicative of proximity of a set of locations in the template image to an edge of the reference polygon; obtaining an inspection image in runtime; identifying first inspection polygons in the inspection image corresponding to the first reference polygons using template images and template masks thereof; determining a first shift for the first layer based on the first locations, and registering the first reference polygons with the inspection image based on the first shift. Similarly, a second shift for the second layer can be determined, and the second reference polygons can be registered with the inspection image based on the second shift.

Shape localization for examining a semiconductor specimen

There is provided a system and method of examination of a semiconductor specimen using an examination recipe. The method includes obtaining a registered image pair, for each design-based structural element associated with a given layer, calculating an edge attribute, using a trained classifier to determine a class of the design-based structural element, and generating a layer score usable to determine validity of the registered image pair. There is also provided a system and method of generating the examination recipe usable for examination of a semiconductor specimen.

Examination of a semiconductor specimen

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Tel Aviv, Israel

Dror Alumot