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    Text recognition for textually sparse images
    1.
    发明授权
    Text recognition for textually sparse images 有权
    文本稀疏图像的文本识别

    公开(公告)号：US09183452B2

    公开(公告)日：2015-11-10

    申请号：US14269777

    申请日：2014-05-05

    Applicant: Google Inc.

    Inventor： Alessandro Bissacco ,  Hartmut Neven

    IPC: G06K9/00 ,  G06K9/34 ,  G06K9/32 ,  G06K9/68

    CPC classification number: G06K9/34 ,  G06K9/32 ,  G06K9/3208 ,  G06K9/3233 ,  G06K9/342 ,  G06K9/6857 ,  G06K2209/01

    Abstract: A text recognition server is configured to recognize text in a sparse text image. Specifically, given an image, the server specifies a plurality of “patches” (blocks of pixels within the image). The system applies a text detection algorithm to the patches to determine a number of the patches that contain text. This application of the text detection algorithm is used both to estimate the orientation of the image and to determine whether the image is textually sparse or textually dense. If the image is determined to be textually sparse, textual patches are identified and grouped into text regions, each of which is then separately processed by an OCR algorithm, and the recognized text for each region is combined into a result for the image as a whole.

    Abstract translation: 文本识别服务器被配置为识别稀疏文本图像中的文本。 具体地，给定图像，服务器指定多个“补丁”（图像内的像素块）。 系统将文本检测算法应用于修补程序，以确定包含文本的多个修补程序。 文本检测算法的这种应用被用于估计图像的取向并确定图像是文本稀疏的还是文本密集的。 如果图像被确定为文本上稀疏的，则文本补丁被识别并分组成文本区域，然后每个文本区域被OCR算法分开处理，并且将每个区域的识别文本合并为整个图像的结果 。

    Object detection with false positive filtering
    2.
    发明授权
    Object detection with false positive filtering 有权
    假阳性滤波对象检测

    公开(公告)号：US09104914B1

    公开(公告)日：2015-08-11

    申请号：US14278450

    申请日：2014-05-15

    Applicant: Google Inc.

    Inventor： Luc Vincent ,  Bo Wu ,  Ahmad Abdulkader ,  Marco Zennaro ,  Alessandro Bissacco ,  Hartwig Adam ,  Kong Man Cheung ,  Hartmut Neven ,  Andrea Lynn Frome

    IPC: G06K9/00

    CPC classification number: G06K9/00624 ,  G06K9/00228 ,  G06K9/00771 ,  G06K9/00791 ,  G06K9/72 ,  G06K2209/15

    Abstract: Embodiments of this invention relate to detecting and blurring images. In an embodiment, a system detects objects in a photographic image. The system includes an object detector module configured to detect regions of the photographic image that include objects of a particular type at least based on the content of the photographic image. The system further includes a false positive detector module configured to determine whether each region detected by the object detector module includes an object of the particular type at least based on information about the context in which the photographic image was taken.

    Abstract translation: 本发明的实施例涉及检测和模糊图像。 在一个实施例中，系统检测摄影图像中的对象。 该系统包括对象检测器模块，其被配置为至少基于摄影图像的内容来检测包括特定类型的对象的摄影图像的区域。 所述系统还包括假阳性检测器模块，其被配置为至少基于关于拍摄照片的上下文的信息来确定由对象检测器模块检测到的每个区域是否包括特定类型的对象。

    FIDELITY ESTIMATION FOR QUANTUM COMPUTING SYSTEMS
    4.
    发明申请
    FIDELITY ESTIMATION FOR QUANTUM COMPUTING SYSTEMS 审中-公开

    公开(公告)号：US20190156239A1

    公开(公告)日：2019-05-23

    申请号：US16301863

    申请日：2016-05-17

    Applicant: GOOGLE INC.

    Inventor： John Martinis ,  Nan Ding ,  Ryan Babbush ,  Sergei V. Isakov ,  Hartmut Neven ,  Vadim Smelyanskiy ,  Sergio Boixo Castrillo

    IPC: G06N10/00

    Abstract: Methods and apparatus for estimating the fidelity of quantum hardware. In one aspect, a method includes accessing a set of quantum gates; sampling a subset of quantum gates from the set of quantum gates, wherein the subset of quantum gates defines a quantum circuit; applying the quantum circuit to a quantum system and performing measurements on the quantum system to determine output information of the quantum system; calculating output information of the quantum system based on application of the quantum circuit to the quantum system; and estimating a fidelity of the quantum circuit based on the determined output information and the calculated output information of the quantum system.

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