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公开(公告)号：US20180007250A1
公开(公告)日：2018-01-04
申请号：US15707302
申请日：2017-09-18
Applicant: Google Inc.
Inventor： Ryan M. Rifkin , Daniel Ramage
CPC classification number: H04N5/23203 , G06F3/017 , G06K9/00355 , G06K9/00919 , G10L15/22 , G10L15/26 , G10L2015/223 , H04N5/23219
Abstract: The present disclosure relates to a method for controlling a digital photography system. The method includes obtaining, by a device, image data and audio data. The method also includes identifying one or more objects in the image data and obtaining a transcription of the audio data. The method also includes controlling a future operation of the device based at least on the one or more objects identified in the image data, and the transcription of the audio data.
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公开(公告)号：US09836819B1
公开(公告)日：2017-12-05
申请号：US14984628
申请日：2015-12-30
Applicant: Google Inc.
Inventor： Aaron Michael Donsbach , Benjamin Vanik , Jon Gabriel Clapper , Alison Lentz , Joshua Denali Lovejoy , Robert Douglas Fritz, III , Krzysztof Duleba , Li Zhang , Juston Payne , Emily Anne Fortuna , Iwona Bialynicka-Birula , Blaise Aguera-Arcas , Daniel Ramage , Hugh Brendan McMahan , Oliver Fritz Lange , Jess Holbrook
CPC classification number: G06T11/60 , G06K9/00221 , G06K9/00664 , G06T1/0007 , G06T2207/20084
Abstract: The present disclosure provides an image capture, curation, and editing system that includes a resource-efficient mobile image capture device that continuously captures images. The mobile image capture device is operable to input an image into at least one neural network and to receive at least one descriptor of the desirability of a scene depicted by the image as an output of the at least one neural network. The mobile image capture device is operable to determine, based at least in part on the at least one descriptor of the desirability of the scene of the image, whether to store a second copy of such image and/or one or more contemporaneously captured images in a non-volatile memory of the mobile image capture device or to discard a first copy of such image from a temporary image buffer without storing the second copy of such image in the non-volatile memory.
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公开(公告)号：US20170109322A1
公开(公告)日：2017-04-20
申请号：US15045707
申请日：2016-02-17
Applicant: Google Inc.
Inventor： Hugh Brendan McMahan , Jakub Konecny , Eider Brantly Moore , Daniel Ramage , Blaise H. Aguera-Arcas
CPC classification number: G06F17/17 , G06F17/11 , G06F17/50 , G06F2217/04 , G06N20/00
Abstract: Systems and methods of determining a global model are provided. In particular, one or more local updates can be received from a plurality of user devices. Each local update can be determined by the respective user device based at least in part on one or more data examples stored on the user device. The one or more data examples stored on the plurality of user devices are distributed on an uneven basis, such that no user device includes a representative sample of the overall distribution of data examples. The local updates can then be aggregated to determine a global model.
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公开(公告)号：US20190050749A1
公开(公告)日：2019-02-14
申请号：US15674910
申请日：2017-08-11
Applicant: Google Inc.
Inventor： Pannag Sanketi , Wolfgang Grieskamp , Daniel Ramage , Hrishikesh Aradhye , Shiyu Hu
Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.
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公开(公告)号：US20170041523A1
公开(公告)日：2017-02-09
申请号：US15048360
申请日：2016-02-19
Applicant: Google Inc.
Inventor： Ryan M. Rifkin , Daniel Ramage
CPC classification number: H04N5/23203 , G06F3/00 , G06K9/00355 , G06K9/00919 , G10L15/22 , G10L15/26 , G10L2015/223 , H04N5/23219
Abstract: The present disclosure relates to a method for controlling a digital photography system. The method includes obtaining, by a device, image data and audio data. The method also includes identifying one or more objects in the image data and obtaining a transcription of the audio data. The method also includes controlling a future operation of the device based at least on the one or more objects identified in the image data, and the transcription of the audio data.
Abstract translation: 本公开涉及一种用于控制数字摄影系统的方法。 该方法包括通过设备获得图像数据和音频数据。 该方法还包括识别图像数据中的一个或多个对象并获得音频数据的转录。 该方法还包括至少基于图像数据中识别的一个或多个对象以及音频数据的转录来控制设备的将来操作。
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Patent Agency Ranking
公开(公告)号：US20220004929A1
公开(公告)日：2022-01-06
申请号：US17479364
申请日：2021-09-20
Applicant: Google Inc.
Inventor： Pannag Sanketi , Wolfgang Grieskamp , Daniel Ramage , Hrishikesh Aradhye , Shiyu Hu
Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.
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公开(公告)号：US20170098159A1
公开(公告)日：2017-04-06
申请号：US14872582
申请日：2015-10-01
Applicant: GOOGLE INC.
Inventor： Matthew Sharifi , Daniel Ramage , David Petrou
IPC: G06N5/02 , G06F17/30 , G06F3/0484
CPC classification number: G06N5/02 , G06F3/0481 , G06F3/0482 , G06F3/0484 , G06F3/04895 , G06F9/453 , G06F16/245 , G06N20/00
Abstract: Systems and methods are provided for suggesting actions for selected text based on content displayed on a mobile device. An example method can include converting a selection made via a display device into a query, providing the query to an action suggestion model that is trained to predict an action given a query, each action being associated with a mobile application, receiving one or more predicted actions, and initiating display of the one or more predicted actions on the display device. Another example method can include identifying, from search records, queries where a website is highly ranked, the website being one of a plurality of websites in a mapping of websites to mobile applications. The method can also include generating positive training examples for an action suggestion model from the identified queries, and training the action suggestion model using the positive training examples.
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公开(公告)号：US20140280221A1
公开(公告)日：2014-09-18
申请号：US14206880
申请日：2014-03-12
Applicant: GOOGLE INC.
Inventor： Pi-Chuan Chuang , Daniel Ramage
IPC: G06F17/30
CPC classification number: G06F17/3053 , G06F17/30699 , G06F17/30867 , G06F17/30876
Abstract: A system stores a table mapping users to attributes, and stores a second table mapping the users to products associated with a source domain. The system determines a set of top scoring products for each of the attributes, and creates, using the top scoring products, a model that is predictive of an activity in a target domain, the target domain being separate from the source domain. The system detects a behavior from a particular user accessing the target domain, and generates a personalized prediction for the particular user based on the model, in response to the detecting the behavior.
Abstract translation: 系统存储将用户映射到属性的表，并存储将用户映射到与源域相关联的产品的第二表。 系统为每个属性确定一组最高评分产品，并使用最高评分产品创建一个预测目标域中活动的模型，目标域与源域分离。 系统检测来自访问目标域的特定用户的行为，并且响应于检测到行为而基于模型为特定用户生成个性化预测。
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公开(公告)号：US10970646B2
公开(公告)日：2021-04-06
申请号：US14872582
申请日：2015-10-01
Applicant: GOOGLE INC.
Inventor： Matthew Sharifi , Daniel Ramage , David Petrou
IPC: G06N20/00 , G06F16/245 , G06F3/0481 , G06F9/451 , G06F3/0489 , G06F16/332 , G06F3/0482 , G06F3/0484 , G06N5/02
Abstract: Systems and methods are provided for suggesting actions for selected text based on content displayed on a mobile device. An example method can include converting a selection made via a display device into a query, providing the query to an action suggestion model that is trained to predict an action given a query, each action being associated with a mobile application, receiving one or more predicted actions, and initiating display of the one or more predicted actions on the display device. Another example method can include identifying, from search records, queries where a website is highly ranked, the website being one of a plurality of websites in a mapping of websites to mobile applications. The method can also include generating positive training examples for an action suggestion model from the identified queries, and training the action suggestion model using the positive training examples.
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公开(公告)号：US20190050746A1
公开(公告)日：2019-02-14
申请号：US15674885
申请日：2017-08-11
Applicant: Google Inc.
Inventor： Pannag Sanketi , Wolfgang Grieskamp , Daniel Ramage , Hrishikesh Aradhye
Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a context provider that securely injects context features into collected training examples and/or client-provided input data used to generate predictions/inferences. Thus, the on-device machine learning platform can enable centralized training example collection, model training, and usage of machine-learned models as a service to applications or other clients.
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