-
公开(公告)号：USD821408S1
公开(公告)日：2018-06-26
申请号：US29558592
申请日：2016-03-18
Applicant: GOOGLE INC.
Designer： Xiaohang Wang , Marcus Quintana Mitchell
-
公开(公告)号：US09965754B2
公开(公告)日：2018-05-08
申请号：US14733917
申请日：2015-06-08
Applicant: GOOGLE INC.
Inventor： Glenn Thrope , Xiaohang Wang , Glenn Berntson , Harry Lee Butler, IV
IPC: G06Q20/00 , G06Q20/20 , G01C21/00 , H04W4/02 , G06N3/02 , G01C21/32 , G06Q30/02 , H04W4/00 , G06Q30/00
CPC classification number: G06Q20/204 , G01C21/00 , G01C21/32 , G06N3/02 , G06Q30/0261 , H04W4/027 , H04W4/029 , H04W4/38 , H04W4/80
Abstract: Identifying the geolocation of POS terminals using non-payment events to predict when the geolocation of a computing device at a time when the device detects events corresponds to the geolocation of the terminal. The device monitors for pre-selected events and transmit data to the account system. The account system determines a frequency of the events and it reaches a pre-defined threshold, the account system identifies the location of the terminal by identifying the common geolocation of the events. The identified geolocation is saved so that when a user then enters the location and transmits event data to the account system, the system can compare the geolocation of the event data to the saved geolocation to determine whether the computing device is located at the terminal. If the computing device is located at the terminal, the account system transmits offers or other content for display and use at the identified terminal.
-
公开(公告)号：US09788159B2
公开(公告)日：2017-10-10
申请号：US15420676
申请日：2017-01-31
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Farhan Shamsi , Yakov Okshtein , David Singleton , Debra Lin Repenning , Lixin Zhang , Marcus Alexander Foster
CPC classification number: H04W4/021 , G06F17/3087 , G08B1/08 , H04W4/12 , H04W64/003
Abstract: A geofence management system obtains location data for points of interest. The geofence management system determines, at the option of the user, the location of a user mobile computing device relative to specific points of interest and alerts the user when the user nears the points of interest. The geofence management system, however, determines relationships among the identified points of interest, and associates or “clusters” the points of interest together based on the determined relationships. Rather than establishing separate geofences for multiple points of interest, and then alerting the user each time the user's mobile device enters each geofence boundary, the geofence management system establishes a single geofence boundary for the associated points of interest. When the user's mobile device enters the clustered geofence boundary, the geofence management system notifies the user device to alert the user of the entrance event. The user then receives the clustered, geofence-based alert.
-
公开(公告)号：US20170083797A1
公开(公告)日：2017-03-23
申请号：US15364222
申请日：2016-11-29
Applicant: GOOGLE INC.
Inventor： Sanjiv Kumar , Henry Allan Rowley , Xiaohang Wang , Jose Jeronimo Moreira Rodrigues
CPC classification number: G06K9/6269 , G06K9/00469 , G06K9/00536 , G06K9/18 , G06K9/186 , G06K9/3233 , G06K9/3258 , G06K9/46 , G06K9/6202 , G06K9/6267 , G06K9/66 , G06K2009/4666 , G06K2209/01 , G06Q20/227 , G06Q20/34 , G06T3/0012 , G06T7/11 , G06T2207/20132 , G07F7/0893
Abstract: Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition (“OCR”). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.
-
公开(公告)号：US20170004370A1
公开(公告)日：2017-01-05
申请号：US15267117
申请日：2016-09-15
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Justin Scheiner , Glenn Berntson
CPC classification number: G06K9/18 , G06K7/1447 , G06K9/00442 , G06K9/036 , G06K9/2054 , G06K9/344 , G06K9/62 , G06K9/6255 , G06K9/726 , G06K2209/01
Abstract: Extracting card information comprises a server at an optical character recognition (“OCR”) system that interprets data from a card. The OCR system performs an optical character recognition algorithm an image of a card and performs a data recognition algorithm on a machine-readable code on the image of the card. The OCR system compares a series of extracted alphanumeric characters obtained via the optical character recognition process to data extracted from the machine-readable code via the data recognition process and matches the alphanumeric series of characters to a particular series of characters extracted from the machine-readable code. The OCR system determines if the alphanumeric series and the matching series of characters extracted from the machine-readable code comprise any discrepancies and corrects the alphanumeric series of characters based on the particular series of characters extracted from the machine-readable code upon a determination that a discrepancy exists.
Abstract translation: 提取卡信息包括解释来自卡的数据的光学字符识别（“OCR”）系统的服务器。 OCR系统对卡的图像执行光学字符识别算法，并对卡的图像上的机器可读代码执行数据识别算法。 OCR系统将经由光学字符识别处理获得的一系列提取的字母数字字符与通过数据识别处理从机器可读代码提取的数据进行比较，并将字母数字系列字符与从机器可读取中提取的特定系列字符相匹配 码。 OCR系统确定从机器可读代码提取的字母数字序列和匹配的字符串是否包含任何差异，并且基于从机器可读代码中提取的特定字符序列来校正字母数字系列字符， 存在差异。
-
Patent Agency Ranking
公开(公告)号：US20160267345A1
公开(公告)日：2016-09-15
申请号：US15158520
申请日：2016-05-18
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Farhan Shamsi , Yakov Okshtein , Sanjiv Kumar , Henry Allan Rowley , Marcus Quintana Mitchell , Debra Lin Repenning , Alessandro Bissacco , Justin Scheiner , Leon Palm
CPC classification number: G06K9/3283 , G06K9/00469 , G06K9/18 , G06K9/228 , G06K9/325 , G06K9/40 , G06K2009/363 , G06K2209/01
Abstract: Extracting financial card information with relaxed alignment comprises a method to receive an image of a card, determine one or more edge finder zones in locations of the image, and identify lines in the one or more edge finder zones. The method further identifies one or more quadrilaterals formed by intersections of extrapolations of the identified lines, determines an aspect ratio of the one or more quadrilateral, and compares the determined aspect ratios of the quadrilateral to an expected aspect ratio. The method then identifies a quadrilateral that matches the expected aspect ratio and performs an optical character recognition algorithm on the rectified model. A similar method is performed on multiple cards in an image. The results of the analysis of each of the cards are compared to improve accuracy of the data.
-
7.外观设计公开(公告)号：USD752073S1
公开(公告)日：2016-03-22
申请号：US29459294
申请日：2013-06-27
Applicant: GOOGLE INC.
Designer： Xiaohang Wang , Marcus Quintana Mitchell
-
公开(公告)号：US09292740B2
公开(公告)日：2016-03-22
申请号：US14559888
申请日：2014-12-03
Applicant: GOOGLE INC.
Inventor： Sanjiv Kumar , Xiaohang Wang , Jose Moreira Rodrigues , Farhan Shamsi , Yakov Okshtein , Henry Allan Rowley , Marcus Quintana Mitchell , Zhifei Li
CPC classification number: G06K9/186 , G06K7/10 , G06K9/00469 , G06K9/18 , G06K9/2054 , G06K9/228 , G06K9/6202 , G06K2209/01 , G06Q20/32 , G06Q20/3223 , G06Q20/3276 , G06Q20/34 , G06Q20/36 , H04N1/00307
Abstract: Extracting card data comprises receiving, by one or more computing devices, a digital image of a card; perform an image recognition process on the digital representation of the card; identifying an image in the digital representation of the card; comparing the identified image to an image database comprising a plurality of images and determining that the identified image matches a stored image in the image database; determining a card type associated with the stored image and associating the card type with the card based on the determination that the identified image matches the stored image; and performing a particular optical character recognition algorithm on the digital representation of the card, the particular optical character recognition algorithm being based on the determined card type. Another example uses an issuer identification number to improve data extraction. Another example compares extracted data with user data to improve accuracy.
-
公开(公告)号：US20150186740A1
公开(公告)日：2015-07-02
申请号：US14645410
申请日：2015-03-11
Applicant: GOOGLE INC.
Inventor： Sanjiv Kumar , Henry Allan Rowley , Xiaohang Wang , Jose Jeronimo Moreira Rodrigues
IPC: G06K9/18
CPC classification number: G06K9/6269 , G06K9/00469 , G06K9/00536 , G06K9/18 , G06K9/186 , G06K9/3233 , G06K9/3258 , G06K9/46 , G06K9/6202 , G06K9/6267 , G06K9/66 , G06K2009/4666 , G06K2209/01 , G06Q20/227 , G06Q20/34 , G06T3/0012 , G06T7/11 , G06T2207/20132 , G07F7/0893
Abstract: Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition (“OCR”). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.
-
公开(公告)号：US09049555B2
公开(公告)日：2015-06-02
申请号：US14329812
申请日：2014-07-11
Applicant: GOOGLE INC.
Inventor： Xiaohang Wang , Farhan Shamsi , Yakov Okshtein , David Singleton , Debra Lin Repenning , Lixin Zhang , Marcus Alexander Foster
CPC classification number: H04W4/021 , G06F17/3087 , G08B1/08 , H04W4/12 , H04W64/003
Abstract: A geofence management system obtains location data for points of interest. The geofence management system determines, at the option of the user, the location of a user mobile computing device relative to specific points of interest and alerts the user when the user nears the points of interest. The geofence management system, however, determines relationships among the identified points of interest, and associates or “clusters” the points of interest together based on the determined relationships. Rather than establishing separate geofences for multiple points of interest, and then alerting the user each time the user's mobile device enters each geofence boundary, the geofence management system establishes a single geofence boundary for the associated points of interest. When the user's mobile device enters the clustered geofence boundary, the geofence management system notifies the user device to alert the user of the entrance event. The user then receives the clustered, geofence-based alert.
Abstract translation: 地理围栏管理系统获取兴趣点的位置数据。 地理围栏管理系统可以根据用户的选择确定用户移动计算设备相对于特定兴趣点的位置，并且在用户接近兴趣点时提醒用户。 然而，地理围栏管理系统根据所确定的关系确定所识别的兴趣点之间的关系，以及关联点或“聚集”兴趣点在一起。 而不是为多个兴趣点建立单独的地理围栏，然后每当用户的移动设备进入每个地理围栏边界时提醒用户，地理围栏管理系统为相关联的兴趣点建立单一的地理围栏边界。 当用户的移动设备进入群集地理围栏边界时，地理围栏管理系统通知用户设备提醒用户入口事件。 然后，用户接收基于地理位置的群集警报。
-
-
-
-
-
-
-
-
-
Search Results
91
records
(took 0.027 seconds)
