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公开(公告)号:US11199895B2
公开(公告)日:2021-12-14
申请号:US16234510
申请日:2018-12-27
Applicant: Intel Corporation
Inventor: Patrick Kam-shing Leung , James Hermerding, II , Muhammad Abozaed , Gilad Olswang , Moran Peri , Ido Karavany , William Freelove , Sudheer Nair , Tahi Hollander , Avishai Wagner
IPC: G06F1/26 , G06F1/32 , G06F1/3287 , G06N5/04 , G06N20/00 , G06F1/20 , G06F1/3234 , G06F1/324
Abstract: In one embodiment, a method receives data regarding processing of a workload by a processor. The data is input into a prediction engine configured to classify the data into a plurality of workload classifications. Each workload classification describes different temporal behavior of the workload. Then, the method outputs a prediction for at least one of the plurality of workload classifications, wherein the prediction is used to control performance of the processor in an upcoming period of time.
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公开(公告)号:US11301686B2
公开(公告)日:2022-04-12
申请号:US16417981
申请日:2019-05-21
Applicant: Intel Corporation
Inventor: Ashwin Muppalla , Sanket Save , Subash Sudireddy , Amitai Armon , Lev Faivishevsky , Moty Fania , Tahi Hollander
Abstract: A mechanism is described for facilitating visual anomaly detection without reference in computing environments. An apparatus of embodiments, as described herein, includes one or more processors to select a frame from a sequence of multiple frames associated with a video stream captured by a camera, and dynamically compute a frame confidence score for the frame based on frame training data associated with frame. The one or more processors are further to detect one or more anomalies in the frame when the frame confidence score is less than a frame confidence threshold associated with the frame, where detecting includes dynamically comparing the frame confidence score with the frame confidence threshold through inference using frame field data and the frame training data.
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