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    • 5. 发明申请
    • LARGE-SCALE ASYMMETRIC COMPARISON COMPUTATION FOR BINARY EMBEDDINGS
    • 用于二进制嵌入的大规模不对称计算
    • US20120143853A1
    • 2012-06-07
    • US12960018
    • 2010-12-03
    • Albert GordoFlorent Perronnin
    • Albert GordoFlorent Perronnin
    • G06F17/30
    • G06F17/30247
    • A system and method for comparing a query object and one or more of a set of database objects are provided. The method includes providing quantized representations of database objects. The database objects have each been transformed with a quantized embedding function which is the composition of a real-valued embedding function and a quantization function. The query object is transformed to a representation of the query object in a real-valued embedding space using the real-valued embedding function. Query-dependent estimated distance values are computed for the query object, based on the transformed query object and stored. A comparison (e.g., distance or similarity) measure between the query object and each of the quantized database object representations is computed based on the stored query-dependent estimated distance values. Data is output based on the comparison computation.
    • 提供了一种用于比较查询对象与一组数据库对象中的一个或多个的系统和方法。 该方法包括提供数据库对象的量化表示。 数据库对象每个都已经用量化嵌入函数进行了变换,该嵌入函数是实值嵌入函数和量化函数的组合。 使用实值嵌入函数将查询对象转换为实值嵌入空间中的查询对象的表示。 基于所转换的查询对象并存储查询对象,计算与查询相关的估计距离值。 基于存储的查询相关估计距离值来计算查询对象和每个量化数据库对象表示之间的比较(例如距离或相似度)度量。 基于比较计算输出数据。
    • 6. 发明授权
    • Large-scale asymmetric comparison computation for binary embeddings
    • 二进制嵌入的大规模非对称比较计算
    • US08370338B2
    • 2013-02-05
    • US12960018
    • 2010-12-03
    • Albert GordoFlorent Perronnin
    • Albert GordoFlorent Perronnin
    • G06F17/30
    • G06F17/30247
    • A system and method for comparing a query object and one or more of a set of database objects are provided. The method includes providing quantized representations of database objects. The database objects have each been transformed with a quantized embedding function which is the composition of a real-valued embedding function and a quantization function. The query object is transformed to a representation of the query object in a real-valued embedding space using the real-valued embedding function. Query-dependent estimated distance values are computed for the query object, based on the transformed query object and stored. A comparison (e.g., distance or similarity) measure between the query object and each of the quantized database object representations is computed based on the stored query-dependent estimated distance values. Data is output based on the comparison computation.
    • 提供了一种用于比较查询对象与一组数据库对象中的一个或多个的系统和方法。 该方法包括提供数据库对象的量化表示。 数据库对象每个都已经用量化嵌入函数进行了变换,该量化嵌入函数是实值嵌入函数和量化函数的组合。 使用实值嵌入函数将查询对象转换为实值嵌入空间中的查询对象的表示。 基于所转换的查询对象并存储查询对象,计算与查询相关的估计距离值。 基于存储的与查询相关的估计距离值来计算查询对象和每个量化数据库对象表示之间的比较(例如,距离或相似性)度量。 基于比较计算输出数据。
    • 7. 发明申请
    • UNSTRUCTURED DOCUMENT CLASSIFICATION
    • 未经规定的文件分类
    • US20110137898A1
    • 2011-06-09
    • US12632135
    • 2009-12-07
    • Albert GordoFlorent PerronninFrancois Ragnet
    • Albert GordoFlorent PerronninFrancois Ragnet
    • G06F17/30
    • G06F16/35G06F16/93
    • A document classification method comprises: (i) classifying pages of an input document to generate page classifications; (ii) aggregating the page classifications to generate an input document representation, the aggregating not being based on ordering of the pages; and (iii) classifying the input document based on the input document representation. A page classifier for use in the page classifying operation (i) is trained based on pages of a set of labeled training documents having document classification labels. In some such embodiments, the pages of the set of labeled training documents are not labeled, and the page classifier training comprises: clustering pages of the set of labeled training documents to generate page clusters; and generating the page classifier based on the page clusters.
    • 文档分类方法包括:(i)分类输入文档的页面以生成页面分类; (ii)聚合页面分类以生成输入文档表示,聚合不是基于页面的排序; 和(iii)基于输入文档表示对输入文档进行分类。 用于页面分类操作(i)中的页面分类器基于具有文档分类标签的一组标记的训练文档的页面进行训练。 在一些这样的实施例中,标记的训练文档集合的页面没有被标记,并且页面分类器训练包括:聚集所标识的训练文档集合的页面以生成页面簇; 以及基于页面集群生成页面分类器。
    • 10. 发明授权
    • System and method for object class localization and semantic class based image segmentation
    • 用于对象类定位和基于语义类的图像分割的系统和方法
    • US08111923B2
    • 2012-02-07
    • US12191579
    • 2008-08-14
    • Gabriela CsurkaFlorent Perronnin
    • Gabriela CsurkaFlorent Perronnin
    • G06K9/46G06K9/00G06K9/64
    • G06K9/00624G06K9/342G06K9/4676G06T7/11G06T2207/10024G06T2207/20021G06T2207/30236G06T2207/30252
    • An automated image processing system and method are provided for class-based segmentation of a digital image. The method includes extracting a plurality of patches of an input image. For each patch, at least one feature is extracted. The feature may be a high level feature which is derived from the application of a generative model to a representation of low level feature(s) of the patch. For each patch, and for at least one object class from a set of object classes, a relevance score for the patch, based on the at least one feature, is computed. For at least some or all of the pixels of the image, a relevance score for the at least one object class based on the patch scores is computed. An object class is assigned to each of the pixels based on the computed relevance score for the at least one object class, allowing the image to be segmented and the segments labeled, based on object class.
    • 提供了一种用于数字图像的基于分类的分割的自动图像处理系统和方法。 该方法包括提取输入图像的多个片段。 对于每个补丁,至少提取一个要素。 该特征可以是从生成模型的应用导出到补丁的低级特征的表示的高级特征。 对于每个补丁以及来自一组对象类的至少一个对象类,基于至少一个特征来计算补丁的相关性得分。 对于图像的至少一些或全部像素,计算基于补丁得分的至少一个对象类别的相关度得分。 基于所计算的至少一个对象类的相关性分数,将对象类分配给每个像素,允许根据对象类来分割图像和标记的图像。