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公开(公告)号:US11836968B1
公开(公告)日:2023-12-05
申请号:US18237866
申请日:2023-08-24
Applicant: SAS INSTITUTE INC.
IPC: G06V10/764 , G06T3/40 , G06T7/70 , G06T7/11
CPC classification number: G06V10/764 , G06T3/40 , G06T7/11 , G06T7/70 , G06V2201/07
Abstract: A system, method, and computer-program product includes detecting, via a localization machine learning model, a target object within a scene based on downsampled image data of the scene, identifying a likely position of the target object within original image data of the scene, extracting, from the original image data of the scene, a target sub-image containing the target object, classifying, via an object classification machine learning model, the target object to a probable object class of a plurality of distinct object classes, routing the target image resolution of the target sub-image to a target object-condition machine learning classification model of a plurality of distinct object-condition machine learning classification models, classifying, via the target object-condition machine learning classification model, the target object to a probable object-condition class, and displaying, via a graphical user interface, a representation of the target object in association with the probable object-condition class.
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2.
公开(公告)号:US20240193917A1
公开(公告)日:2024-06-13
申请号:US18528685
申请日:2023-12-04
Applicant: SAS INSTITUTE INC.
IPC: G06V10/764 , G06V10/94
CPC classification number: G06V10/764 , G06V10/94
Abstract: A system, method, and computer-program product includes detecting, via a localization machine learning model, a target object within target image data of a scene, classifying, via an object classification machine learning model, the target object to a probable object class of a plurality of distinct object classes, routing, via the one or more processors, the target image data of the scene to a target object-condition machine learning classification model of a plurality of distinct object-condition machine learning classification models based on a mapping between the plurality of distinct object classes and the plurality of distinct object-condition machine learning classification models, classifying, via the target object-condition machine learning classification model, the target object to a probable object-condition class of a plurality of distinct object-condition classes, and displaying, via a graphical user interface, a representation of the target object in association with the probable object-condition class.
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公开(公告)号:US12002256B1
公开(公告)日:2024-06-04
申请号:US18528685
申请日:2023-12-04
Applicant: SAS INSTITUTE INC.
IPC: G06V10/764 , G06V10/94
CPC classification number: G06V10/764 , G06V10/94
Abstract: A system, method, and computer-program product includes detecting, via a localization machine learning model, a target object within target image data of a scene, classifying, via an object classification machine learning model, the target object to a probable object class of a plurality of distinct object classes, routing, via the one or more processors, the target image data of the scene to a target object-condition machine learning classification model of a plurality of distinct object-condition machine learning classification models based on a mapping between the plurality of distinct object classes and the plurality of distinct object-condition machine learning classification models, classifying, via the target object-condition machine learning classification model, the target object to a probable object-condition class of a plurality of distinct object-condition classes, and displaying, via a graphical user interface, a representation of the target object in association with the probable object-condition class.
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