-
公开(公告)号：US20240078801A1
公开(公告)日：2024-03-07
申请号：US18220182
申请日：2023-07-10
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson
IPC分类号： G06V10/82 , G06F18/214 , G06F18/2415 , G06F18/40 , G06T7/13 , G06T7/143 , G06V10/44 , G06V10/50
CPC分类号： G06V10/82 , G06F18/2148 , G06F18/2415 , G06F18/40 , G06T7/13 , G06T7/143 , G06V10/44 , G06V10/507 , G06T2207/20076 , G06T2207/20081 , G06T2207/20084
摘要： This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.
-
2.发明申请公开(公告)号：US20200005069A1
公开(公告)日：2020-01-02
申请号：US16433602
申请日：2019-06-06
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson , David Y. Li
摘要： This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.
-
公开(公告)号：US20190139225A1
公开(公告)日：2019-05-09
申请号：US16001885
申请日：2018-06-06
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson
摘要： This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.
-
公开(公告)号：US10937168B2
公开(公告)日：2021-03-02
申请号：US16001885
申请日：2018-06-06
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson
摘要： This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.
-
公开(公告)号：US11699283B2
公开(公告)日：2023-07-11
申请号：US17127889
申请日：2020-12-18
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson
IPC分类号： G06T19/00 , G06T7/13 , G06T7/143 , G06V10/44 , G06V10/50 , G06V10/82 , G06F18/40 , G06F18/214 , G06F18/2415 , G06K9/62
CPC分类号： G06V10/82 , G06F18/2148 , G06F18/2415 , G06F18/40 , G06T7/13 , G06T7/143 , G06V10/44 , G06V10/507 , G06T2207/20076 , G06T2207/20081 , G06T2207/20084
摘要： This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.
-
公开(公告)号：US11568629B2
公开(公告)日：2023-01-31
申请号：US16433602
申请日：2019-06-06
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson , David Y. Li
摘要： This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.
-
公开(公告)号：US20210233250A1
公开(公告)日：2021-07-29
申请号：US17127889
申请日：2020-12-18
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson
摘要： This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.
-
8.发明公开公开(公告)号：US20240005148A1
公开(公告)日：2024-01-04
申请号：US18103432
申请日：2023-01-30
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson , David Y. Li
IPC分类号： G06N3/08 , G06V10/50 , G06F18/214 , G06V10/82 , G06V10/44
CPC分类号： G06N3/08 , G06V10/50 , G06F18/2148 , G06V10/7553 , G06V10/454 , G06V10/44 , G06V10/82
摘要： This invention provides a system and method for finding patterns in images that incorporates neural net classifiers. A pattern finding tool is coupled with a classifier that can be run before or after the tool to have labeled pattern results with sub-pixel accuracy. In the case of a pattern finding tool that can detect multiple templates, its performance is improved when a neural net classifier informs the pattern finding tool to work only on a subset of the originally trained templates. Similarly, in the case of a pattern finding tool that initially detects a pattern, a neural network classifier can then determine whether it has found the correct pattern. The neural network can also reconstruct/clean-up an imaged shape, and/or to eliminate pixels less relevant to the shape of interest, therefore reducing the search time, as well significantly increasing the chance of lock on the correct shapes.
-
公开(公告)号：US10657650B2
公开(公告)日：2020-05-19
申请号：US16001885
申请日：2018-06-06
申请人： Cognex Corporation
发明人： Lei Wang , Vivek Anand , Lowell D. Jacobson
摘要： This invention provides a system and method for finding line features in an image that allows multiple lines to be efficiently and accurately identified and characterized. When lines are identified, the user can train the system to associate predetermined (e.g. text) labels with respect to such lines. These labels can be used to define neural net classifiers. The neural net operates at runtime to identify and score lines in a runtime image that are found using a line-finding process. The found lines can be displayed to the user with labels and an associated probability score map based upon the neural net results. Lines that are not labeled are generally deemed to have a low score, and are either not flagged by the interface, or identified as not relevant.
-
-
-
-
-
-
-
-
搜索结果
9 条记录 (耗时 0.011 秒)
