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    Semiconductor Device With Dual Types of Zero Cost Embedded Memory
    122.
    发明申请
    Semiconductor Device With Dual Types of Zero Cost Embedded Memory 审中-公开

    公开(公告)号：US20200168740A1

    公开(公告)日：2020-05-28

    申请号：US16775507

    申请日：2020-01-29

    Applicant: David Liu

    Inventor： David Liu

    IPC: H01L29/788 ,  H01L29/78 ,  H01L27/11521 ,  H01L29/66 ,  H01L29/10 ,  H01L27/11541 ,  H01L27/11558 ,  H01L29/423

    Abstract: An integrated circuit includes two different types of embedded memories, with cells that have different retention characteristics, and situated in different areas of the substrate. In some applications the cells are both non-volatile memories sharing a common gate layer but with different oxide layers, different thicknesses, etc. The first type of cell is a conventional flash cell which can be part of a logic/memory region, while the second type of cell uses capacitive coupling and can be located in a high voltage region. Because of their common features, the need for additional masks, manufacturing steps, etc. can be mitigated.

    Automatic valid vote count storage using secure embedded non volatile memory
    123.
    发明授权
    Automatic valid vote count storage using secure embedded non volatile memory 有权
    使用安全嵌入式非易失性存储器进行自动有效投票计数存储

    公开(公告)号：US09064192B2

    公开(公告)日：2015-06-23

    申请号：US13475555

    申请日：2012-05-18

    Applicant: David Liu

    Inventor： David Liu

    IPC: G06K17/00 ,  G07C13/00

    CPC classification number: G07C13/00 ,  G06K17/00 ,  G06Q10/00 ,  G06Q2220/10 ,  G06Q2230/00 ,  G11C16/0408

    Abstract: A non-volatile memory system adapted for securely registering votes within a voting system is described. The votes are encoded as a set of logically grouped cells based on a voter's selection of an item. The encoding assures that the votes are easily distinguishable by a read circuit.

    Abstract translation: 描述了适于在投票系统内安全地登记投票的非易失性存储器系统。 投票根据选民的项目选择编码为一组逻辑分组的单元格。 编码确保投票可以通过读取电路轻松区分。

    Method and system for training a landmark detector using multiple instance learning
    125.
    发明授权
    Method and system for training a landmark detector using multiple instance learning 有权
    使用多实例学习训练地标探测器的方法和系统

    公开(公告)号：US08588519B2

    公开(公告)日：2013-11-19

    申请号：US13228509

    申请日：2011-09-09

    Applicant: David Liu ,  Shaohua Kevin Zhou ,  Paul Swoboda ,  Dorin Comaniciu ,  Christian Tietjen

    Inventor： David Liu ,  Shaohua Kevin Zhou ,  Paul Swoboda ,  Dorin Comaniciu ,  Christian Tietjen

    IPC: G06K9/52

    CPC classification number: G06K9/6257 ,  G06K2209/051

    Abstract: An apparatus and method for training a landmark detector receives training data which includes a plurality of positive training bags, each including a plurality of positively annotated instances, and a plurality of negative training bags, each including at least one negatively annotated instance. Classification function is initialized by training a first weak classifier based on the positive training bags and the negative training bags. All training instances are evaluated using the classification function. For each of a plurality of remaining classifiers, a cost value gradient is calculated based on spatial context information of each instance in each positive bag evaluated by the classification function. A gradient value associated with each of the remaining weak classifiers is calculated based on the cost value gradients, and a weak classifier is selected which has a lowest associated gradient value and given a weighting parameter and added to the classification function.

    Abstract translation: 用于训练地标检测器的装置和方法接收训练数据，训练数据包括多个正训练袋，每个正训练袋包括多个带有正面注释的实例，以及多个负训练袋，每个包括至少一个负注释实例。 基于积极的训练袋和负面训练袋训练第一个弱分类器来初始化分类功能。 使用分类函数评估所有训练实例。 对于多个剩余分类器中的每一个，基于由分类函数评估的每个正包中的每个实例的空间上下文信息来计算成本值梯度。 基于成本值梯度计算与剩余弱分类器中的每一个相关联的梯度值，并且选择具有最低相关梯度值并给出加权参数并加到分类函数的弱分类器。

    Systems and methods for determining prescribing physician activity levels
    127.
    发明授权
    Systems and methods for determining prescribing physician activity levels 有权
    用于确定处方医师活动水平的系统和方法

    公开(公告)号：US08386276B1

    公开(公告)日：2013-02-26

    申请号：US12704209

    申请日：2010-02-11

    Applicant: David Liu ,  Sean Daniel Reisz ,  Thomas A. Picard

    Inventor： David Liu ,  Sean Daniel Reisz ,  Thomas A. Picard

    IPC: G06Q10/00 ,  G06Q50/00

    CPC classification number: G06Q50/22 ,  G06F19/00

    Abstract: Systems and methods may determine prescribing physician activity levels. Information associated with a plurality of healthcare transaction requests that are received during a designated time period from at least one healthcare provider computer for communication to one or more claims processor computers may be collected. A respective prescribing physician for each of the plurality of received healthcare transaction requests may be identified. For each identified physician, a respective activity measure for the designated time period may be calculated based upon a respective number of the healthcare transaction requests identifying the physician.

    Abstract translation: 系统和方法可以确定处方医师活动水平。 可以收集与从至少一个医疗保健提供者计算机通信到一个或多个权利要求处理器计算机的指定时间段期间接收到的多个保健交易请求相关联的信息。 可以识别针对多个接收到的医疗保健交易请求中的每一个的相应处方医师。 对于每个识别的医师，可以基于识别医师的医疗保健交易请求的相应数量来计算指定时间段的相应活动度量。

    Automatic Valid Vote Count Storage using Secure Embedded Non Volatile Memory
    128.
    发明申请
    Automatic Valid Vote Count Storage using Secure Embedded Non Volatile Memory 有权
    使用安全嵌入式非易失性存储器的自动有效投票计数存储

    公开(公告)号：US20120296706A1

    公开(公告)日：2012-11-22

    申请号：US13475555

    申请日：2012-05-18

    Applicant: David Liu

    Inventor： David Liu

    IPC: G07C13/00 ,  G06Q90/00

    CPC classification number: G07C13/00 ,  G06K17/00 ,  G06Q10/00 ,  G06Q2220/10 ,  G06Q2230/00 ,  G11C16/0408

    Abstract: A non-volatile memory system adapted for securely registering votes within a voting system is described. The votes are encoded as a set of logically grouped cells based on a voter's selection of an item. The encoding assures that the votes are easily distinguishable by a read circuit.

    Abstract translation: 描述了适于在投票系统内安全地登记投票的非易失性存储器系统。 投票根据选民的项目选择编码为一组逻辑分组的单元格。 编码确保投票可以通过读取电路轻松区分。

    Feature selection and extraction
    129.
    发明授权
    Feature selection and extraction 有权
    特征选择和提取

    公开(公告)号：US08244044B2

    公开(公告)日：2012-08-14

    申请号：US12109347

    申请日：2008-04-25

    Applicant: Gang Hua ,  Paul Viola ,  David Liu

    Inventor： Gang Hua ,  Paul Viola ,  David Liu

    IPC: G06K9/62 ,  G06K9/46

    CPC classification number: G06K9/4647 ,  G06K9/468 ,  G06K9/6228

    Abstract: Image feature selection and extraction (e.g., for image classifier training) is accomplished in an integrated manner, such that higher-order features are merely developed from first-order features selected for image classification. That is, first-order image features are selected for image classification from an image feature pool, initially populated with pre-extracted first-order image features. The selected first-order classifying features are paired with previously selected first-order classifying features to generate higher-order features. The higher-order features are placed into the image feature pool as they are developed or “on-the-fly” (e.g., for use in image classifier training).

    Abstract translation: 图像特征选择和提取（例如，用于图像分类器训练）以集成的方式实现，使得仅从为图像分类选择的一阶特征开发高阶特征。 也就是说，从图像特征池中选择用于图像分类的一阶图像特征，最初用预提取的一阶图像特征填充。 所选择的一阶分类特征与先前选择的一阶分类特征配对以产生更高阶的特征。 更高阶的特征被放置在图像特征池中，因为它们被开发或“即时”（例如，用于图像分类器训练）。

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