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    • 24. 发明申请
    • GENERATING PIXEL MAPS FROM NON-IMAGE DATA AND DIFFERENCE METRICS FOR PIXEL MAPS
    • 从像素图的非图像数据和差异度量生成像素图
    • WO2018013533A1
    • 2018-01-18
    • PCT/US2017/041489
    • 2017-07-11
    • THE CLIMATE CORPORATION
    • ZHONG, HaoXU, Ying
    • A01D45/00A01G1/00G01C11/04G06Q50/02G06T7/00
    • Systems and methods for scalable comparisons between two pixel maps are provided. In an embodiment, an agricultural intelligence computer system generates pixel maps from non-image data by transforming a plurality of values and location values into pixel values and pixel locations. The agricultural intelligence computer system converts each pixel map into a vector of values. The agricultural intelligence computer system also generates a matrix of metric coefficients where each value in the matrix of metric coefficients is computed using a spatial distance between to pixel locations in one of the pixel maps. Using the vectors of values and the matrix of metric coefficients, the agricultural intelligence computer system generates a difference metric identifying a difference between the two pixel maps. In an embodiment, the difference metric is normalized so that the difference metric is scalable to pixel maps of different sizes.
    • 提供了用于两个像素图之间的可缩放比较的系统和方法。 在一个实施例中,农业智能计算机系统通过将多个值和位置值转换成像素值和像素位置,从非图像数据生成像素图。 农业智能计算机系统将每个像素图转换成值的向量。 农业智能计算机系统还生成度量系数矩阵,其中度量系数矩阵中的每个值使用像素地图之一中的像素位置之间的空间距离来计算。 使用值的向量和度量系数矩阵,农业智能计算机系统生成识别两个像素图之间差异的差异度量。 在一个实施例中,差异度量被标准化,使得差异度量可缩放到不同尺寸的像素映射。
    • 28. 发明申请
    • CROWDSOURCED SEARCH AND LOCATE PLATFORM
    • CROWDSOURCED搜索和定位平台
    • WO2014130591A1
    • 2014-08-28
    • PCT/US2014/017229
    • 2014-02-19
    • DIGITALGLOBE, INC.BARRINGTON, LukeHAR-NOY, ShayRICKLIN, Nathan
    • BARRINGTON, LukeHAR-NOY, ShayRICKLIN, Nathan
    • G06K9/46G01C11/04
    • G01C11/04
    • A crowdsourced search and locate platform, comprising an application server and a crowdrank server. The application server: receives connections from crowdsourcing participants; navigates a first crowdsourcing participant to a specific geospatial location; sends an image corresponding to the geospatial location to the first crowdsourcing participant; receives tagging data from the first crowdsourcing participant, the tagging data corresponding to a plurality of objects and locations identified by the first crowdsourcing participant. The crowdrank server: retrieves a plurality of tags made by participating users computes agreement and disagreement values for each of the plurality of retrieved tags; performs an expectation-maximization or expectation-minimization process iteratively until a configured maximum number of iterations is performed or until an indicia of rate of change between iterations falls below a configured threshold; and provides resulting output values corresponding to geolocations of objects of a plurality of types to an administrative user.
    • 众包的搜索和定位平台,包括应用服务器和人群化服务器。 应用服务器:从众包参与者接收连接; 将第一个众包参与者导航到特定的地理空间位置; 将对应于地理空间位置的图像发送给第一众包参与者; 从第一众包参与者接收标签数据,对应于由第一众包参与者识别的多个对象和位置的标记数据。 人群化服务器:检索由参与用户制作的多个标签计算多个检索标签中的每一个的协议和不一致值; 迭代地执行期望最大化或期望最小化处理,直到执行配置的最大迭代次数,或者直到迭代之间的变化率的标记低于配置的阈值为止; 并向管理用户提供与多种类型的对象的地理位置对应的结果输出值。