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    SYSTEMS AND METHODS FOR ANALYZING REMOTE SENSING IMAGERY
    1.
    发明申请
    SYSTEMS AND METHODS FOR ANALYZING REMOTE SENSING IMAGERY 审中-公开

    公开(公告)号：US20190213413A1

    公开(公告)日：2019-07-11

    申请号：US16353361

    申请日：2019-03-14

    申请人： Cape Analytics, Inc.

    发明人： Ryan KOTTENSTETTE ,  Peter LORENZEN ,  Suat GEDIKLI

    IPC分类号： G06K9/00 ,  G06K9/62 ,  G06K9/46

    CPC分类号： G06K9/00637 ,  G06K9/4623 ,  G06K9/627 ,  H04N5/332

    摘要： Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.

    OBJECT DETECTION APPARATUS, OBJECT DETECTION METHOD, AND STORAGE MEDIUM
    3.
    发明申请
    OBJECT DETECTION APPARATUS, OBJECT DETECTION METHOD, AND STORAGE MEDIUM 审中-公开

    公开(公告)号：US20170236030A1

    公开(公告)日：2017-08-17

    申请号：US15583631

    申请日：2017-05-01

    申请人： CANON KABUSHIKI KAISHA

    发明人： Masao Yamanaka ,  Masakazu Matsugu ,  Katsuhiko Mori

    IPC分类号： G06K9/46 ,  G06K9/32 ,  G06K9/20

    CPC分类号： G06K9/4671 ,  G06K9/2054 ,  G06K9/3233 ,  G06K9/4609 ,  G06K9/4623 ,  G06K9/4661

    摘要： An object detection apparatus first sets a first partial region having a preset size and a second partial region in a given point (pixel) in an input image. In addition, the object detection apparatus calculates a first information amount in the second partial region, and sets a third partial region based on the size of the first information amount. Furthermore, the object detection apparatus calculates a score based on a salience degree that is based on a difference in statistical feature amount distribution between the first partial region and the second partial region, and based on an information amount of feature amount in the third partial region. Lastly, the object detection apparatus detects a main object by calculating scores on the respective points in the image and applying a predetermined statistical process to the scores.

    SYSTEMS AND METHODS FOR ANALYZING REMOTE SENSING IMAGERY
    5.
    发明申请
    SYSTEMS AND METHODS FOR ANALYZING REMOTE SENSING IMAGERY 审中-公开
    用于分析远程感测图像的系统和方法

    公开(公告)号：US20170076438A1

    公开(公告)日：2017-03-16

    申请号：US15253488

    申请日：2016-08-31

    申请人： Cape Analytics, Inc.

    发明人： Ryan KOTTENSTETTE ,  Peter LORENZEN ,  Suat GEDIKLI

    IPC分类号： G06T7/00 ,  H04N5/33 ,  G06K9/46 ,  G06K9/62

    CPC分类号： G06K9/00637 ,  G06K9/4623 ,  G06K9/627 ,  H04N5/332

    摘要： Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.

    摘要翻译： 公开的系统和方法涉及遥感，深度学习和物体检测。 一些实施例涉及用于对象检测的机器学习，其包括例如识别目标图像中的像素类并且基于参数集生成标签图像。 其他实施例涉及用于几何提取的机器学习，其包括例如确定目标图像中的一个或多个区域的高度并确定目标图像中的几何对象属性。 其他实施例涉及用于对准的机器学习，其包括例如经由变换参数的直接或间接估计对准图像。

    CONTEXT-AWARENESS THROUGH BIASED ON-DEVICE IMAGE CLASSIFIERS
    7.
    发明申请
    CONTEXT-AWARENESS THROUGH BIASED ON-DEVICE IMAGE CLASSIFIERS 审中-公开
    通过偏移的设备图像分类器的背景 - 意识

    公开(公告)号：US20160267324A1

    公开(公告)日：2016-09-15

    申请号：US14715555

    申请日：2015-05-18

    申请人： MICROSOFT TECHNOLOGY LICENSING, LLC

    发明人： Mohammed SHOAIB ,  Jie LIU ,  Jin LI

    IPC分类号： G06K9/00 ,  H04N1/00 ,  H04N5/225

    CPC分类号： G06K9/00536 ,  G06K9/00523 ,  G06K9/00986 ,  G06K9/4623 ,  G06K9/4671 ,  G06K2009/4666 ,  H04N1/00204 ,  H04N1/00244

    摘要： Examples of the disclosure enable efficient processing of images. One or more features are extracted from a plurality of images. Based on the extracted features, the plurality of images are classified into a first set including a plurality of first images and a second set including a plurality of second images. One or more images of the plurality of first images are false positives. The plurality of first images and none of the plurality of second images are transmitted to a remote device. The remote device is configured to process one or more images including recognizing the extracted features, understanding the images, and/or generating one or more actionable items. Aspects of the disclosure facilitate conserving memory at a local device, reducing processor load or an amount of energy consumed at the local device, and/or reducing network bandwidth usage between the local device and the remote device.

    摘要翻译： 本公开的示例使得能够有效地处理图像。 从多个图像中提取一个或多个特征。 基于提取的特征，将多个图像分类为包括多个第一图像的第一组和包括多个第二图像的第二组。 多个第一图像中的一个或多个图像是假阳性。 多个第一图像和多个第二图像中的任一个被发送到远程设备。 远程设备被配置为处理一个或多个图像，包括识别所提取的特征，理解图像和/或生成一个或多个可操作的项目。 本公开的方面有助于节省本地设备的存储器，减少本地设备的处理器负载或消耗的能量的量，和/或减少本地设备与远程设备之间的网络带宽使用。

    IMAGE PROCESSING
    9.
    发明申请
    IMAGE PROCESSING 审中-公开
    图像处理

    公开(公告)号：US20160189396A1

    公开(公告)日：2016-06-30

    申请号：US15066972

    申请日：2016-03-10

    申请人： Cortexica Vision Systems Limited

    发明人： Jeffrey Ng Sing KWONG ,  Spyridon GIDARIS ,  Yin LI ,  Anil Anthony BHARATH ,  Muhammad AWAIS ,  Eduardo VAZQUEZ ,  Yu QIAN

    IPC分类号： G06T7/40 ,  G06K9/46

    CPC分类号： G06T7/44 ,  G06K9/4623 ,  G06K9/4652 ,  G06T2207/10024

    摘要： A method of generating a descriptor of at least part of an image includes receiving image data representing the at least part of the image. The image data is processed to identify at least one texture characteristic of the at least part of the image, thereby generating texture data indicative of a texture of the at least part of the image. The texture data is processed with the image data, thereby generating weighted texture data. A descriptor of the at least part of the image is generated using the weighted texture data.

    摘要翻译： 产生图像的至少一部分的描述符的方法包括接收表示图像的至少一部分的图像数据。 处理图像数据以识别图像的至少部分的至少一个纹理特征，从而生成指示图像的至少部分的纹理的纹理数据。 用图像数据处理纹理数据，从而生成加权纹理数据。 使用加权纹理数据生成图像的至少部分的描述符。

    METHOD AND APPARATUS FOR DETECTING SALIENT REGION OF IMAGE
    10.
    发明申请
    METHOD AND APPARATUS FOR DETECTING SALIENT REGION OF IMAGE 有权
    用于检测图像区域的方法和装置

    公开(公告)号：US20150227816A1

    公开(公告)日：2015-08-13

    申请号：US14581418

    申请日：2014-12-23

    申请人： Huawei Technologies Co., Ltd.

    发明人： Xinyu DU ,  Dong WANG ,  Zichen GU ,  Daiyu WEI

    IPC分类号： G06K9/62 ,  G06K9/48 ,  G06K9/46 ,  G06T7/40 ,  G06K9/66 ,  G06T7/00

    CPC分类号： G06K9/623 ,  G06K9/4623 ,  G06K9/4642 ,  G06K9/4652 ,  G06K9/481 ,  G06K9/6256 ,  G06K9/66 ,  G06K9/80 ,  G06T2207/10024 ,  G06T2207/20081 ,  G06T2207/20164

    摘要： The present invention provides a method and an apparatus for detecting a salient region of an image. Classification processing is performed on a test image according to an image feature vector of the test image by using a classifier obtained by means of pre-training, so as to obtain a classification label, where the classification label is used to indicate a salience detection algorithm for detecting a salient region of the test image. Salience detection is performed on the test image by using the salience detection algorithm indicated by the classification label, so as to obtain the salient region of the test image. Because a salience detection algorithm with the best detection effect is acquired by using the image feature vector of the test image, to detect the salient region of the test image, accuracy of salience detection is improved.

    摘要翻译： 本发明提供一种用于检测图像的显着区域的方法和装置。 通过使用通过预训练获得的分类器，根据测试图像的图像特征向量对测试图像执行分类处理，以获得分类标签，其中分类标签用于指示突出检测算法 用于检测测试图像的显着区域。 通过使用由分类标签指示的突出检测算法，对测试图像进​​行显着性检测，以获得测试图像的显着区域。 因为通过使用测试图像的图像特征向量来获取具有最佳检测效果的突出检测算法，以检测测试图像的显着区域，提高了显着性检测的准确性。