Kla Tencor Corporation

Ping Gu

Lisheng Gao

Allen Park

Kris Bhaskar

Songnian Rong

Ashok V Kulkarni

Kenong Wu

Tao-Yi Fu

Ellis Chang

Grace Hsiu-Ling Chen

Jing Zhang

Saibal Banerjee

Grace H Chen

Junqing Huang

Keith B Wells

Khurram Zafar

Xuguang Jiang

Sylvain Muckenhirn

Christopher Maher

Steve R Lange

Liu-Ming Wu

Nan Bai

Methods and systems for generating a high resolution image for a specimen from one or more low resolution images of the specimen are provided. One system includes one or more computer subsystems configured for acquiring one or more low resolution images of a specimen. The system also includes one or more components executed by the one or more computer subsystems. The one or more components include a model that includes one or more first layers configured for generating a representation of the one or more low resolution images. The model also includes one or more second layers configured for generating a high resolution image of the specimen from the representation of the one or more low resolution images.

Generating high resolution images from low resolution images for semiconductor applications

Methods and systems for monitoring a non-defect related characteristic of a patterned wafer are provided. One computer-implemented method includes generating output responsive to light from a patterned wafer using an inspection system. The method also includes determining differences between a value of a non-defect related characteristic of the patterned wafer and a known value of the non-defect related characteristic based on differences between one or more attributes of the output and one or more attributes of other output of the inspection system for a different patterned wafer having the known value of the non-defect related characteristic.

Methods and systems for monitoring a non-defect related characteristic of a patterned wafer

Methods and systems for detecting anomalies in images of a specimen are provided. One system includes one or more computer subsystems configured for acquiring images generated of a specimen by an imaging subsystem. The computer subsystem(s) are also configured for determining one or more characteristics of the acquired images. In addition, the computer subsystem(s) are configured for identifying anomalies in the images based on the one or more determined characteristics without applying a defect detection algorithm to the images or the one or more characteristics of the images.

Image based specimen process control

The present invention includes searching imagery data in order to identify one or more patterned regions on a semiconductor wafer, generating one or more virtual Fourier filter (VFF) working areas, acquiring an initial set of imagery data from the VFF working areas, defining VFF training blocks within the identified patterned regions of the VFF working areas utilizing the initial set of imagery data, wherein each VFF training block is defined to encompass a portion of the identified patterned region displaying a selected repeating pattern, calculating an initial spectrum for each VFF training block utilizing the initial set of imagery data from the VFF training blocks, and generating a VFF for each training block by identifying frequencies of the initial spectrum having maxima in the frequency domain, wherein the VFF is configured to null the magnitude of the initial spectrum at the frequencies identified to display spectral maxima.

Region based virtual fourier filter

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San Jose, CA, United States of America

Ping Gu