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公开(公告)号：US20230136291A1
公开(公告)日：2023-05-04
申请号：US17514549
申请日：2021-10-29
Applicant: Intel Corporation
Inventor： Fabian Boemer , Vinodh Gopal , Gelila Seifu , Sejun Kim , Jack Crawford
Abstract: A processor includes an instruction set architecture that having instructions to perform data parallel multiply on a set of 52-bit integers and further instructions that additionally perform an add or subtract on intermediate products of the data parallel multiply. A 52-bit result of the operations is then zero extended to 64-bits.
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Patent Agency Ranking
公开(公告)号：US20180322333A1
公开(公告)日：2018-11-08
申请号：US15587194
申请日：2017-05-04
Applicant: Intel Corporation
Inventor： Chaunte W. Lacewell , Ravishankar R. Iyer , Sejun Kim
CPC classification number: G06K9/00295 , G06K9/627 , G06K9/6274 , G06N20/00
Abstract: A system and related method are provided for sensor-based person recognition. The system has a data store including global data of a user, the global data including a globally unique identifier and sensed training data. The system further has a classifier to identify the user at a first time using the global data, augment the global data with first context information of the user captured at the first time, and identify the user at a second time by finding correlations between second context information and the first context information when using the global data fails, the second context information of the user captured at the second time.
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公开(公告)号：US10860853B2
公开(公告)日：2020-12-08
申请号：US15582106
申请日：2017-04-28
Applicant: Intel Corporation
Inventor： Carl S. Marshall , Ravishankar Iyer , Sejun Kim , Doye C. Emelue
Abstract: Methods, apparatus, and system to enable and implement interaction between a computer device and a person (or people) such as via images and objects identified in such images. The interaction may make possible rapid and convenient machine learning with respect to such objects.
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公开(公告)号：US20230140257A1
公开(公告)日：2023-05-04
申请号：US17514523
申请日：2021-10-29
Applicant: Intel Corporation
Inventor： Fabian Boemer , Vinodh Gopal , Gelila Seifu , Sejun Kim , Jack Crawford
IPC: G06F9/30
Abstract: One embodiment provides a processor comprising first circuitry to decode an instruction into a decoded instruction, the instruction to indicate a first source operand, a second source operand and a third operand, and second circuitry including a processing resource to execute the decoded instruction. Responsive to the decoded instruction, the processing resource is to output a result of a modular addition operation based on a data element of first source operand data plus a data element of second source operand data modulo a data element of third operand data, provided that the data elements of the first operand data and second operand data are less than the data element of the third operand data.
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公开(公告)号：US20230081763A1
公开(公告)日：2023-03-16
申请号：US17476726
申请日：2021-09-16
Applicant: Intel Corporation
Inventor： Fabian Boemer , Vinodh Gopal , Gelila Seifu , Sejun Kim , Jack Crawford
Abstract: One embodiment provides a processor comprising first circuitry to decode an instruction into a decoded instruction, the instruction to indicate a first source operand and a second source operand and second circuitry including a processing resource to execute the decoded instruction, wherein responsive to the decoded instruction, the processing resource is to output a result of first source operand data minus second source operand data in response to a determination by the processing resource that the first source operand data is greater than or equal to the second source operand data, otherwise the processing resource is to output the first source operand data.
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公开(公告)号：US10671840B2
公开(公告)日：2020-06-02
申请号：US15587194
申请日：2017-05-04
Applicant: Intel Corporation
Inventor： Chaunte W. Lacewell , Ravishankar R. Iyer , Sejun Kim
Abstract: A system and related method are provided for sensor-based person recognition. The system has a data store including global data of a user, the global data including a globally unique identifier and sensed training data. The system further has a classifier to identify the user at a first time using the global data, augment the global data with first context information of the user captured at the first time, and identify the user at a second time by finding correlations between second context information and the first context information when using the global data fails, the second context information of the user captured at the second time.
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