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公开(公告)号：US20210349038A1
公开(公告)日：2021-11-11
申请号：US17136919
申请日：2020-12-29
Applicant: KLA Corporation
Inventor： Brian Duffy , Mark Roulo , Ashok Mathew , Jing Zhang , Kris Bhaskar
Abstract: An inspection system is disclosed. The inspection system includes a shared memory configured to receive image data from a defect inspection tool and a controller communicatively coupled to the shared memory. The controller includes a host image module configured to apply one or more general-purpose defect-inspection algorithms to the image data using central-processing unit (CPU) architectures, a results module configured to generate inspection data for defects identified by the host image module, and secondary image module(s) configured to apply one or more targeted defect-inspection algorithms to the image data. The secondary image module(s) employ flexible sampling of the image data to match a data processing rate of the host image module within a selected tolerance. The flexible sampling of the image data is adjusted responsive to the inspection data generated by the results module and the host image module.
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公开(公告)号：US20250020598A1
公开(公告)日：2025-01-16
申请号：US18646704
申请日：2024-04-25
Applicant: KLA Corporation
Inventor： Rajkumar Theagarajan , Yujie Dong , Jing Zhang , Brian Duffy , Atiqur Rahman Chowdhury , Kris Bhaskar , Yang Li , Graham Jensen
Abstract: Methods and systems for determining information for a specimen are provided. One system includes a computer subsystem and one or more components executed by the computer subsystem that include a setup deep learning (DL) model configured for separately performing defect detection for a specimen based on output generated for the specimen by each of two or more modes of an inspection system, respectively, and separately re-performing defect detection for the specimen based on masked output generated for each of the modes, respectively. The computer subsystem determines a difference between results of separately performing and separately re-performing the defect detections for each of the modes, respectively, and identifies a subset of the modes for which the difference is larger than other modes as candidate mode(s) for inspection of the specimen.
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公开(公告)号：US11415526B2
公开(公告)日：2022-08-16
申请号：US17136919
申请日：2020-12-29
Applicant: KLA Corporation
Inventor： Brian Duffy , Mark Roulo , Ashok Mathew , Jing Zhang , Kris Bhaskar
Abstract: An inspection system is disclosed. The inspection system includes a shared memory configured to receive image data from a defect inspection tool and a controller communicatively coupled to the shared memory. The controller includes a host image module configured to apply one or more general-purpose defect-inspection algorithms to the image data using central-processing unit (CPU) architectures, a results module configured to generate inspection data for defects identified by the host image module, and secondary image module(s) configured to apply one or more targeted defect-inspection algorithms to the image data. The secondary image module(s) employ flexible sampling of the image data to match a data processing rate of the host image module within a selected tolerance. The flexible sampling of the image data is adjusted responsive to the inspection data generated by the results module and the host image module.
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Patent Agency Ranking
公开(公告)号：US20210366103A1
公开(公告)日：2021-11-25
申请号：US17128502
申请日：2020-12-21
Applicant: KLA Corporation
Inventor： Jing Zhang , Yujie Dong , Vishank Bhatia , Patrick McBride , Kris Bhaskar , Brian Duffy
Abstract: A system may be configured for joint defect discovery and optical mode selection. Defects are detected during a defect discovery step. The discovered defects are accumulated into a mode selection dataset. The mode selection dataset is used to perform mode selection to determine a mode combination. The mode combination may then be used to train the defect detection model. Additional defects may then be detected by the defect detection model. The additional defects may then be provided to the mode selection dataset, for further performing mode selection and training the defect detection model. One or more run-time modes may then be determined. The system may be configured for mode selection and defect detection at an image pixel level.
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公开(公告)号：US11769242B2
公开(公告)日：2023-09-26
申请号：US17128502
申请日：2020-12-21
Applicant: KLA Corporation
Inventor： Jing Zhang , Yujie Dong , Vishank Bhatia , Patrick McBride , Kris Bhaskar , Brian Duffy
CPC classification number: G06T7/0004 , G01N21/9501 , G06T2207/20081 , G06T2207/20084 , G06T2207/30148
Abstract: A system may be configured for joint defect discovery and optical mode selection. Defects are detected during a defect discovery step. The discovered defects are accumulated into a mode selection dataset. The mode selection dataset is used to perform mode selection to determine a mode combination. The mode combination may then be used to train the defect detection model. Additional defects may then be detected by the defect detection model. The additional defects may then be provided to the mode selection dataset, for further performing mode selection and training the defect detection model. One or more run-time modes may then be determined. The system may be configured for mode selection and defect detection at an image pixel level.
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6.发明公开公开(公告)号：US20240169116A1
公开(公告)日：2024-05-23
申请号：US18334357
申请日：2023-06-13
Applicant: KLA Corporation
Inventor： Brian Duffy , Kris Bhaskar
IPC: G06F30/20 , G06F30/3308
CPC classification number: G06F30/20 , G06F30/3308
Abstract: Methods and systems for performing functions with protected data sources from different entities are provided. One system includes a virtual system coupled to an actual system to thereby receive output generated by the actual system for a physical version of the specimen while the specimen is disposed within the actual system. The virtual system includes at least a computer system and a storage medium. The virtual system is not capable of having the physical version of the specimen disposed therein. The virtual system is configured for performing one or more functions for the specimen with two or more protected data sources from two or more different entities, respectively. The virtual system is also configured for performing a virtual version of a process capable of being performed by the actual system for the physical version of the specimen.
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公开(公告)号：US11922619B2
公开(公告)日：2024-03-05
申请号：US18128140
申请日：2023-03-29
Applicant: KLA Corporation
Inventor： Brian Duffy , Bradley Ries , Laurent Karsenti , Kuljit S. Virk , Asaf J. Elron , Ruslan Berdichevsky , Oriel Ben Shmuel , Shlomi Fenster , Yakir Gorski , Oren Dovrat , Ron Dekel , Emanuel Garbin , Sasha Smekhov
IPC: G06T7/00
CPC classification number: G06T7/001 , G06T2207/20076 , G06T2207/20084 , G06T2207/30148
Abstract: A context-based inspection system is disclosed. The system may include an optical imaging sub-system. The system may further include one or more controllers communicatively coupled to the optical imaging system. The one or more controllers may be configured to: receive one or more reference images; receive one or more test images of a sample; generate one or more probabilistic context maps during inspection runtime using an unsupervised classifier; provide the generated one or more probabilistic context maps to a supervised classifier during the inspection runtime; and apply the supervised classifier to the received one or more test images to identify one or more DOIs on the sample.
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公开(公告)号：US20230316500A1
公开(公告)日：2023-10-05
申请号：US18128140
申请日：2023-03-29
Applicant: KLA Corporation
Inventor： Brian Duffy , Bradley Ries , Laurent Karsenti , Kuljit S. Virk , Asaf J. Elron , Ruslan Berdichevsky , Oriel Ben Shmuel , Shlomi Fenster , Yakir Gorski , Oren Dovrat , Ron Dekel , Emanuel Garbin , Sasha Smekhov
IPC: G06T7/00
CPC classification number: G06T7/001 , G06T2207/20076 , G06T2207/20084 , G06T2207/30148
Abstract: A context-based inspection system is disclosed. The system may include an optical imaging sub-system. The system may further include one or more controllers communicatively coupled to the optical imaging system. The one or more controllers may be configured to: receive one or more reference images; receive one or more test images of a sample; generate one or more probabilistic context maps during inspection runtime using an unsupervised classifier; provide the generated one or more probabilistic context maps to a supervised classifier during the inspection runtime; and apply the supervised classifier to the received one or more test images to identify one or more DOIs on the sample.
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