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    Apparatus and method for predicting solar irradiance variation
    2.
    发明授权
    Apparatus and method for predicting solar irradiance variation 有权
    用于预测太阳辐照度变化的装置和方法

    公开(公告)号：US08923567B2

    公开(公告)日：2014-12-30

    申请号：US13329450

    申请日：2011-12-19

    申请人： Yi Yao ,  Peter Tu ,  Ming-Ching Chang ,  Li Guan ,  Yan Tong

    发明人： Yi Yao ,  Peter Tu ,  Ming-Ching Chang ,  Li Guan ,  Yan Tong

    IPC分类号： G06K9/00

    CPC分类号： G01W1/10 ,  F24S50/00 ,  F24S2201/00 ,  H01L31/02021 ,  Y02E10/40 ,  Y02E10/50

    摘要： An apparatus and method, as may be used for predicting solar irradiance variation, are provided. The apparatus may include a solar irradiance predictor processor (10) configured to process a sequence of images (e.g., sky images). The irradiance predictor processor may include a cloud classifier module (18) configured to classify respective pixels of an image of a cloud to indicate a solar irradiance-passing characteristic of at least a portion of the cloud. A cloud motion predictor (22) may be configured to predict motion of the cloud over a time horizon. An event predictor (24) may be configured to predict over the time horizon occurrence of a solar obscuration event. The prediction of the solar obscuration event may be based on the predicted motion of the cloud. The event predictor may include an irradiance variation prediction for the obscuration event based on the solar irradiance-passing characteristic of the cloud.

    摘要翻译： 提供了可用于预测太阳辐照度变化的装置和方法。 该装置可以包括被配置为处理图像序列（例如，天空图像）的太阳辐照度预测器处理器（10）。 辐照度预测器处理器可以包括云分类器模块（18），其被配置为对云的图像的各个像素进行分类，以指示云的至少一部分的太阳辐射通过特性。 云运动预测器（22）可以被配置为预测云在时间范围内的运动。 事件预测器（24）可以被配置为在太阳遮挡事件的时间范围内发生预测。 太阳遮蔽事件的预测可以基于云的预测运动。 事件预测器可以包括基于云的太阳辐射通过特性的遮蔽事件的辐照度变化预测。

    USAGE MEASURENT TECHNIQUES AND SYSTEMS FOR INTERACTIVE ADVERTISING
    3.
    发明申请
    USAGE MEASURENT TECHNIQUES AND SYSTEMS FOR INTERACTIVE ADVERTISING 审中-公开
    用于互动广告的测量技术和系统

    公开(公告)号：US20130138499A1

    公开(公告)日：2013-05-30

    申请号：US13308386

    申请日：2011-11-30

    申请人： Peter Henry Tu ,  Mark Lewis Grabb ,  Xiaoming Liu ,  Ting Yu ,  Yi Yao ,  Dashan Gao ,  Ming-Ching Chang

    发明人： Peter Henry Tu ,  Mark Lewis Grabb ,  Xiaoming Liu ,  Ting Yu ,  Yi Yao ,  Dashan Gao ,  Ming-Ching Chang

    IPC分类号： G06Q30/02

    摘要： An advertising system is disclosed. In one embodiment, the system includes an advertising display configured to provide an advertisement to potential customers and a camera configured to capture images of the potential customers when the potential customers pass the advertising display. The system may also include an image processing system having a processor and a memory. The memory may include application instructions for execution by the processor, and the image processing system may be configured to execute the application instructions to derive usage characteristics of the potential customers with respect to the advertising display through analysis of the captured images. Additional methods, systems, and articles of manufacture are also disclosed.

    摘要翻译： 公开了广告系统。 在一个实施例中，系统包括被配置为向潜在客户提供广告的广告显示器和被配置为当潜在客户通过广告显示时捕获潜在客户的图像的照相机。 该系统还可以包括具有处理器和存储器的图像处理系统。 存储器可以包括用于由处理器执行的应用指令，并且图像处理系统可以被配置为执行应用指令以通过分析所捕获的图像来导出相对于广告显示的潜在客户的使用特性。 还公开了附加的方法，系统和制品。

    Action-based models to identify learned tasks
    4.
    发明授权
    Action-based models to identify learned tasks 有权
    基于行动的模型识别学习任务

    公开(公告)号：US09384448B2

    公开(公告)日：2016-07-05

    申请号：US13339297

    申请日：2011-12-28

    申请人： Peter Henry Tu ,  Ting Yu ,  Dashan Gao ,  Thomas Baby Sebastian ,  Yi Yao

    发明人： Peter Henry Tu ,  Ting Yu ,  Dashan Gao ,  Thomas Baby Sebastian ,  Yi Yao

    IPC分类号： G06N99/00 ,  G06K9/62

    CPC分类号： G06N99/005 ,  G06K9/6256

    摘要： Systems provided herein include a learning environment and an agent. The learning environment includes an avatar and an object. A state signal corresponding to a state of the learning environment includes a location and orientation of the avatar and the object. The agent is adapted to receive the state signal, to issue an action capable of generating at least one change in the state of the learning environment, to produce a set of observations relevant to a task, to hypothesize a set of action models configured to explain the observations, and to vet the set of action models to identify a learned model for the task.

    摘要翻译： 本文提供的系统包括学习环境和代理。 学习环境包括头像和对象。 对应于学习环境的状态的状态信号包括化身和对象的位置和方向。 该代理适于接收状态信号，以发出能够产生学习环境状态的至少一个变化的动作，以产生与任务相关的一组观察结果，以假设一组动作模型，其被配置为解释 观察，并且审视一套动作模型，以确定一个学习的任务模型。

    APPARATUS AND METHOD FOR PREDICTING SOLAR IRRADIANCE VARIATION
    5.
    发明申请
    APPARATUS AND METHOD FOR PREDICTING SOLAR IRRADIANCE VARIATION 有权
    用于预测太阳辐射变化的装置和方法

    公开(公告)号：US20130152997A1

    公开(公告)日：2013-06-20

    申请号：US13329450

    申请日：2011-12-19

    申请人： Yi Yao ,  Peter Tu ,  Ming-Ching Chang ,  Li Guan ,  Yan Tong

    发明人： Yi Yao ,  Peter Tu ,  Ming-Ching Chang ,  Li Guan ,  Yan Tong

    IPC分类号： G06K9/00 ,  H01L31/042

    CPC分类号： G01W1/10 ,  F24S50/00 ,  F24S2201/00 ,  H01L31/02021 ,  Y02E10/40 ,  Y02E10/50

    摘要： An apparatus and method, as may be used for predicting solar irradiance variation, are provided. The apparatus may include a solar irradiance predictor processor (10) configured to process a sequence of images (e.g., sky images). The irradiance predictor processor may include a cloud classifier module (18) configured to classify respective pixels of an image of a cloud to indicate a solar irradiance-passing characteristic of at least a portion of the cloud. A cloud motion predictor (22) may be configured to predict motion of the cloud over a time horizon. An event predictor (24) may be configured to predict over the time horizon occurrence of a solar obscuration event. The prediction of the solar obscuration event may be based on the predicted motion of the cloud. The event predictor may include an irradiance variation prediction for the obscuration event based on the solar irradiance-passing characteristic of the cloud.

    摘要翻译： 提供了可用于预测太阳辐照度变化的装置和方法。 该装置可以包括被配置为处理图像序列（例如，天空图像）的太阳辐照度预测器处理器（10）。 辐照度预测器处理器可以包括云分类器模块（18），其被配置为对云的图像的各个像素进行分类，以指示云的至少一部分的太阳辐射通过特性。 云运动预测器（22）可以被配置为预测云在时间范围内的运动。 事件预测器（24）可以被配置为在太阳遮挡事件的时间范围内发生预测。 太阳遮蔽事件的预测可以基于云的预测运动。 事件预测器可以包括基于云的太阳辐射通过特性的遮蔽事件的辐照度变化预测。

    System, method and program product for camera-based object analysis
    7.
    发明授权
    System, method and program product for camera-based object analysis 有权
    用于基于相机的对象分析的系统，方法和程序产品

    公开(公告)号：US07953245B2

    公开(公告)日：2011-05-31

    申请号：US12542994

    申请日：2009-08-18

    申请人： Gianfranco Doretto ,  Yi Yao

    发明人： Gianfranco Doretto ,  Yi Yao

    IPC分类号： G06K9/62

    CPC分类号： G06K9/525 ,  G06K9/00637

    摘要： A system, method and program product for camera-based object analyses including object recognition, object detection, and/or object categorization. An exemplary embodiment of the computerized method for analyzing objects in images obtained from a camera system includes receiving image(s) having pixels from the camera system; calculating a pool of features for each pixel; then deriving either a pool of radial moment of features from the pool of features and a geometric center of the image(s) or a pool of central moments of features from the pool of features; then calculating a normalized descriptor, based on an area of the image(s) and either of the derived pool of moments of features; and then based on the normalized descriptor, a computer then either recognizes, detects, and/or categorizes an object(s) in the image(s).

    摘要翻译： 一种用于基于相机的对象分析的系统，方法和程序产品，包括对象识别，对象检测和/或对象分类。 用于分析从相机系统获得的图像中的物体的计算机化方法的示例性实施例包括从相机系统接收具有像素的图像; 计算每个像素的特征池; 然后从特征池中获得特征的径向力矩池，以及图像的几何中心或来自特征池的特征的中心时刻池; 然后基于图像的面积和所导出的特征矩的任一个来计算归一化描述符; 然后基于归一化描述符，计算机然后识别，检测和/或分类图像中的对象。

    DAS Same-Well Monitoring Real-Time Microseismic Effective Event Identification Method Based on Deep Learning
    9.
    发明公开
    DAS Same-Well Monitoring Real-Time Microseismic Effective Event Identification Method Based on Deep Learning 审中-公开

    公开(公告)号：US20230296800A1

    公开(公告)日：2023-09-21

    申请号：US18324104

    申请日：2023-05-25

    申请人： Yikang Zheng ,  Yibo Wang ,  Shaojiang Wu ,  Yi Yao

    发明人： Yikang Zheng ,  Yibo Wang ,  Shaojiang Wu ,  Yi Yao

    IPC分类号： G01V1/48

    CPC分类号： G01V1/48 ,  G06N3/084

    摘要： Embodiments of the present disclosure provide a DAS same-well monitoring real-time microseismic effective event identification method based on deep learning, comprising: constructing a DAS-based horizontal well microseismic monitoring system; constructing a training data set, comprising microseismic event data, pipe wave data and background noise data with different types of labels; constructing a signal identification module; training the signal identification module by using the training data set; preprocessing actual monitoring data, inputting the preprocessed data into the signal identification module to obtain an output result; marking microseismic events identified in the output result, and updating the marked microseismic events into the training data set; and adjusting and updating the signal identification module. The identification method according to the present disclosure can identify microseismic events in DAS same-well monitoring data in real time and efficiently.