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    RECOMMENDING ANALYTIC TASKS BASED ON SIMILARITY OF DATASETS
    11.
    发明申请
    RECOMMENDING ANALYTIC TASKS BASED ON SIMILARITY OF DATASETS 审中-公开

    公开(公告)号：US20180181641A1

    公开(公告)日：2018-06-28

    申请号：US15580430

    申请日：2015-06-23

    申请人： ENTIT Software LLC

    发明人： Mahashweta Das ,  Mehmet Kivanc Ozonat

    IPC分类号： G06F17/30 ,  G06F9/48 ,  G06N99/00

    CPC分类号： G06F16/285 ,  G06F9/4881 ,  G06F16/245 ,  G06K9/6215 ,  G06K9/6218 ,  G06K9/6227 ,  G06N20/00

    摘要： Recommending analytic tasks based on similarity of datasets is disclosed. One example is a system including a data processor, a matching module, and a recommendation module. The data processor receives an incoming dataset via a processing system, and generates a feature vector for the incoming dataset. The matching module determines similarity measures between the generated feature vector and representative feature vectors for a plurality of datasets in a data repository, and selects at least one dataset of the plurality of datasets based on the similarity measures. The recommendation module identifies at least one analytic task associated with the selected dataset, and recommends, to a computing device via the processing system, the at least one analytic task to be performed on the incoming dataset.

    Identity authentication by using human biological characteristic
    14.
    发明授权
    Identity authentication by using human biological characteristic 有权

    公开(公告)号：US09930533B2

    公开(公告)日：2018-03-27

    申请号：US15371523

    申请日：2016-12-07

    申请人： Alibaba Group Holding Limited

    发明人： Weian Jin ,  Mian Huang ,  Xiaoling Li

    IPC分类号： H04L29/06 ,  H04W12/08 ,  G06K9/00 ,  G06K9/62 ,  G06F21/32 ,  H04W12/06

    CPC分类号： H04W12/08 ,  G06F21/32 ,  G06K9/00087 ,  G06K9/00885 ,  G06K9/00926 ,  G06K9/6227 ,  G06K2009/00583 ,  H04L63/0861 ,  H04W12/06

    摘要： A human biological characteristic file corresponding to a particular identity is received and used as a base file. A characteristic code to be authenticated is obtained according to a human biological characteristic of a person who requests identity authentication when an identity authentication request corresponding to the particular identity is received. A base characteristic code is collected from a base file. A collecting algorithm applied for collecting the base characteristic code is the same as or matches an algorithm applied for obtaining the characteristic code. The present techniques determine whether the base characteristic code and the characteristic code correspond to a same human biological characteristic. If a result is positive, the identity authentication request is verified. The present techniques implement communication between different terminal devices of different manufacturers and effectively improve user experiences, thereby efficiently and conveniently implementing remote identity authentication.

    LOW- AND HIGH-FIDELITY CLASSIFIERS APPLIED TO ROAD-SCENE IMAGES
    17.
    发明申请
    LOW- AND HIGH-FIDELITY CLASSIFIERS APPLIED TO ROAD-SCENE IMAGES 审中-公开

    公开(公告)号：US20170200063A1

    公开(公告)日：2017-07-13

    申请号：US14995134

    申请日：2016-01-13

    申请人： Ford Global Technologies, LLC

    发明人： Vidya Nariyambut Murali ,  Madeline Jane Schrier

    IPC分类号： G06K9/62 ,  G06T1/20 ,  G06K9/00

    CPC分类号： G06K9/6227 ,  G06K9/00818 ,  G06K9/4628 ,  G06K9/6274 ,  G06N3/0454 ,  G06N3/084 ,  G06T1/20 ,  G06T2207/30252

    摘要： Disclosures herein teach applying a set of sections spanning a down-sampled version of an image of a road-scene to a low-fidelity classifier to determine a set of candidate sections for depicting one or more objects in a set of classes. The set of candidate sections of the down-sampled version may be mapped to a set of potential sectors in a high-fidelity version of the image. A high-fidelity classifier may be used to vet the set of potential sectors, determining the presence of one or more objects from the set of classes. The low-fidelity classifier may include a first Convolution Neural Network (CNN) trained on a first training set of down-sampled versions of cropped images of objects in the set of classes. Similarly, the high-fidelity classifier may include a second CNN trained on a second training set of high-fidelity versions of cropped images of objects in the set of classes.

    ENHANCING HANDWRITING RECOGNITION USING PRE-FILTER CLASSIFICATION
    20.
    发明申请
    ENHANCING HANDWRITING RECOGNITION USING PRE-FILTER CLASSIFICATION 审中-公开
    使用预过滤器分类来增强手写识别

    公开(公告)号：US20170068868A1

    公开(公告)日：2017-03-09

    申请号：US14849162

    申请日：2015-09-09

    申请人： Google Inc.

    发明人： Victor Carbune ,  Thomas Deselaers ,  Daniel M. Keysers

    IPC分类号： G06K9/22 ,  G06F17/27

    CPC分类号： G06K9/222 ,  G06F17/275 ,  G06K9/00422 ,  G06K9/6227 ,  G06K9/6807

    摘要： Methods, systems, and devices, including computer programs encoded on a computer storage medium, for improving handwriting detection. In one aspect, a method includes receiving data indicating one or more strokes, determining one or more features of the one or more strokes, determining whether the one or more strokes likely represent a grapheme based at least on one or more of the features, selecting a particular recognition process for processing the data, from among (i) a multi-language recognition process which processes input strokes using multiple recognizers that are each trained to output, for a given set of input strokes, one or more graphemes that are associated with a particular language, and (ii) a single character, universal recognition process which processes input strokes using a universal recognizer that is trained to output, for a given set of input strokes, a single grapheme, and providing the data to the particular recognition process.

    摘要翻译： 方法，系统和设备，包括在计算机存储介质上编码的计算机程序，用于改进手写检测。 一方面，一种方法包括接收指示一个或多个笔画的数据，确定一个或多个笔画的一个或多个特征，基于至少一个或多个特征来确定所述一个或多个笔画是否可能代表图形，选择 用于处理数据的特定识别过程，从（i）对于给定的一组输入笔画处理输入笔画的多语言识别处理，所述多语言识别处理处理输入笔画使用多个识别器，所述多个识别器被训练以输出给定的一组输入笔画，所述一个或多个字母与 特定语言，以及（ii）单个字符的通用识别过程，其使用通用识别器来处理输入笔画，所述通用识别器被训练为针对给定的一组输入笔画输出单个字母，并且将数据提供给特定识别过程 。