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Patent Agency Ranking
1.发明授权公开(公告)号：US10324046B1
公开(公告)日：2019-06-18
申请号：US15241005
申请日：2016-08-18
Applicant: KLA-Tencor Corporation
Inventor： Tao-Yi Fu , Steve Lange , Lisheng Gao , Xuguang Jiang , Ping Gu , Sylvain Muckenhirn
Abstract: 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.
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公开(公告)号：US10181185B2
公开(公告)日：2019-01-15
申请号：US15402197
申请日：2017-01-09
Applicant: KLA-Tencor Corporation
Inventor： Allen Park , Lisheng Gao , Ashok Kulkarni , Saibal Banerjee , Ping Gu , Songnian Rong , Kris Bhaskar
Abstract: 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.
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公开(公告)号：US20170200264A1
公开(公告)日：2017-07-13
申请号：US15402197
申请日：2017-01-09
Applicant: KLA-Tencor Corporation
Inventor： Allen Park , Lisheng Gao , Ashok Kulkarni , Saibal Banerjee , Ping Gu , Songnian Rong , Kris Bhaskar
IPC: G06T7/00
CPC classification number: G06T7/0004 , G01N21/9501 , G06T7/001 , G06T2207/10056 , G06T2207/10061 , G06T2207/20081 , G06T2207/20084 , G06T2207/30148
Abstract: 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.
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4.发明申请公开(公告)号：US20170193680A1
公开(公告)日：2017-07-06
申请号：US15396800
申请日：2017-01-02
Applicant: KLA-Tencor Corporation
Inventor： Jing Zhang , Grace Hsiu-Ling Chen , Kris Bhaskar , Keith Wells , Nan Bai , Ping Gu , Lisheng Gao
CPC classification number: G01N21/9501 , G01N2201/12 , G06K9/4628 , G06K9/6273 , G06K9/6857 , G06K2209/19 , G06T3/4053
Abstract: 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.
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5.发明授权公开(公告)号：US10648924B2
公开(公告)日：2020-05-12
申请号：US15396800
申请日：2017-01-02
Applicant: KLA-Tencor Corporation
Inventor： Jing Zhang , Grace Hsiu-Ling Chen , Kris Bhaskar , Keith Wells , Nan Bai , Ping Gu , Lisheng Gao
Abstract: 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.
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