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    Execution allocation cost assessment for computing systems and environments including elastic computing systems and environments
    4.
    发明授权
    Execution allocation cost assessment for computing systems and environments including elastic computing systems and environments 有权
    包括弹性计算系统和环境在内的计算系统和环境的执行分配成本评估

    公开(公告)号：US09576240B2

    公开(公告)日：2017-02-21

    申请号：US14020711

    申请日：2013-09-06

    申请人： SAMSUNG ELECTRONICS CO., LTD.

    发明人： Sangoh Jeong ,  Simon J. Gibbs ,  Xinwen Zhang ,  Anugeetha Kunjithapatham

    IPC分类号： G06N5/02 ,  G06F9/50

    CPC分类号： G06N5/02 ,  G06F9/5066

    摘要： Techniques for allocating individually executable portions of executable code for execution in an Elastic computing environment are disclosed. In an Elastic computing environment, scalable and dynamic external computing resources can be used in order to effectively extend the computing capabilities beyond that which can be provided by internal computing resources of a computing system or environment. Machine learning can be used to automatically determine whether to allocate each individual portion of executable code (e.g., a Weblet) for execution to either internal computing resources of a computing system (e.g., a computing device) or external resources of an dynamically scalable computing resource (e.g., a Cloud). By way of example, status and preference data can be used to train a supervised learning mechanism to allow a computing device to automatically allocate executable code to internal and external computing resources of an Elastic computing environment.

    摘要翻译： 公开了用于在弹性计算环境中分配用于执行的可执行代码的单独可执行部分的技术。 在弹性计算环境中，可以使用可扩展和动态的外部计算资源，以便有效地将计算能力扩展到可以由计算系统或环境的内部计算资源提供的能力。 机器学习可用于自动确定是否将可执行代码（例如，Weblet）的每个单独部分分配给计算系统（例如，计算设备）的内部计算资源或动态可扩展计算资源的外部资源 （例如，云）。 作为示例，状态和偏好数据可以用于训练监督学习机制，以允许计算设备自动地将可执行代码分配给弹性计算环境的内部和外部计算资源。

    Selecting a behavior of a virtual agent
    6.
    发明授权
    Selecting a behavior of a virtual agent 有权

    公开(公告)号：US10664741B2

    公开(公告)日：2020-05-26

    申请号：US14996030

    申请日：2016-01-14

    申请人： Samsung Electronics Co., Ltd.

    发明人： Simon J. Gibbs ,  Anthony Liot ,  Yu Song

    IPC分类号： G06N3/00 ,  G06T13/40 ,  G06F9/451 ,  G06F3/16

    摘要： In one aspect, a method for operating a virtual agent will be described. An interaction context is obtained. An agent state is determined based on the obtained interaction context. The agent state indicates an activity of the virtual agent. The emotion of the virtual agent is updated based on the obtained interaction context, the determined agent state and/or a personality of the virtual agent. One or more behaviors are selected. Each behavior involves or indicates a change in an appearance of the virtual agent or generation of audio. Various embodiments relate to devices, servers, software and systems arranged to implement one or more of the above operations.

    VISION INTELLIGENCE MANAGEMENT FOR ELECTRONIC DEVICES
    7.
    发明申请
    VISION INTELLIGENCE MANAGEMENT FOR ELECTRONIC DEVICES 审中-公开

    公开(公告)号：US20180204061A1

    公开(公告)日：2018-07-19

    申请号：US15875393

    申请日：2018-01-19

    申请人： Samsung Electronics Co., Ltd.

    发明人： Stanislaw Antol ,  Abhijit Bendale ,  Simon J. Gibbs ,  Won J. Jeon ,  Hyun Jae Kang ,  Jihee Kim ,  Bo Li ,  Anthony S. Liot ,  Lu Luo ,  Pranav K. Mistry ,  Zhihan Ying

    IPC分类号： G06K9/00 ,  G06K9/66 ,  G06K9/62 ,  G06F11/34 ,  G06K9/32

    摘要： One embodiment provides a method comprising classifying one or more objects present in an input comprising visual data by executing a first set of models associated with a domain on the input. Each model corresponds to an object category. Each model is trained to generate a visual classifier result relating to a corresponding object category in the input with an associated confidence value indicative of accuracy of the visual classifier result. The method further comprises aggregating a first set of visual classifier results based on confidence value associated with each visual classifier result of each model of the first set of models. At least one other model is selectable for execution on the input based on the aggregated first set of visual classifier results for additional classification of the objects. One or more visual classifier results are returned to an application running on an electronic device for display.

    EXECUTION ALLOCATION COST ASSESSMENT FOR COMPUTING SYSTEMS AND ENVIRONMENTS INCLUDING ELASTIC COMPUTING SYSTEMS AND ENVIRONMENTS
    9.
    发明申请
    EXECUTION ALLOCATION COST ASSESSMENT FOR COMPUTING SYSTEMS AND ENVIRONMENTS INCLUDING ELASTIC COMPUTING SYSTEMS AND ENVIRONMENTS 有权
    包括弹性计算系统和环境在内的计算系统和环境的执行成本分摊费用评估

    公开(公告)号：US20140074763A1

    公开(公告)日：2014-03-13

    申请号：US14020711

    申请日：2013-09-06

    申请人： SAMSUNG ELECTRONICS CO., LTD.

    发明人： Sangoh Jeong ,  Simon J. Gibbs ,  Xinwen Zhang ,  Anugeetha Kunjithaptham

    IPC分类号： G06N5/02

    CPC分类号： G06N5/02 ,  G06F9/5066

    摘要： Techniques for allocating individually executable portions of executable code for execution in an Elastic computing environment are disclosed. In an Elastic computing environment, scalable and dynamic external computing resources can be used in order to effectively extend the computing capabilities beyond that which can be provided by internal computing resources of a computing system or environment. Machine learning can be used to automatically determine whether to allocate each individual portion of executable code (e.g., a Weblet) for execution to either internal computing resources of a computing system (e.g., a computing device) or external resources of an dynamically scalable computing resource (e.g., a Cloud). By way of example, status and preference data can be used to train a supervised learning mechanism to allow a computing device to automatically allocate executable code to internal and external computing resources of an Elastic computing environment.

    摘要翻译： 公开了用于在弹性计算环境中分配用于执行的可执行代码的单独可执行部分的技术。 在弹性计算环境中，可以使用可扩展和动态的外部计算资源，以便有效地将计算能力扩展到可以由计算系统或环境的内部计算资源提供的能力。 机器学习可用于自动确定是否将可执行代码（例如，Weblet）的每个单独部分分配给计算系统（例如，计算设备）的内部计算资源或动态可扩展计算资源的外部资源 （例如，云）。 作为示例，状态和偏好数据可以用于训练监督学习机制，以允许计算设备自动地将可执行代码分配给弹性计算环境的内部和外部计算资源。

    BROWSER ENGINE INTERFACING FOR ACCELERATED PHYSICS ENGINE
    10.
    发明申请
    BROWSER ENGINE INTERFACING FOR ACCELERATED PHYSICS ENGINE 有权
    用于加速物理发动机的BROWSER发动机接口

    公开(公告)号：US20130304791A1

    公开(公告)日：2013-11-14

    申请号：US13888220

    申请日：2013-05-06

    申请人： SAMSUNG ELECTRONICS CO., LTD.

    发明人： Tasneem Brutch ,  Simon J. Gibbs ,  Chang Shu

    IPC分类号： H04L29/08

    CPC分类号： H04L67/10 ,  G06F9/541 ,  G06F9/547 ,  G06F17/30867

    摘要： A method for application interfacing a native physics engine includes embedding access to a native physics engine within a browser engine. Bindings are provided for supporting multiple application classes from the browser engine to the native physics engine and a JavaScript engine.

    摘要翻译： 一种应用接口本机物理引擎的方法包括嵌入对浏览器引擎内的本机物理引擎的访问。 提供了绑定，用于支持从浏览器引擎到本机物理引擎和JavaScript引擎的多个应用程序类。