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公开(公告)号：US09852363B1
公开(公告)日：2017-12-26
申请号：US14987955
申请日：2016-01-05
Applicant: Google Inc.
Inventor： Jonathon Shlens , Quoc V. Le , Gregory Sean Corrado , Marc'Aurelio Ranzato
CPC classification number: G06K9/627 , G06F17/30244 , G06F17/30247 , G06F17/30268 , G06F17/3079 , G06F17/30843 , G06K9/6215 , G06K9/6255 , G06K9/6256
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating labeled images. One of the methods includes selecting a plurality of candidate videos from videos identified in a response to a search query derived from a label for an object category; selecting one or more initial frames from each of the candidate videos; detecting one or more initial images of objects in the object category in the initial frames; for each initial frame including an initial image of an object in the object category, tracking the object through surrounding frames to identify additional images of the object; and selecting one or more images from the one or more initial images and one or more additional images as database images of objects belonging to the object category.
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公开(公告)号：US20160117316A1
公开(公告)日：2016-04-28
申请号：US14921925
申请日：2015-10-23
Applicant: Google Inc.
Inventor： Quoc V. Le , Minh-Thang Luong , Ilya Sutskever , Oriol Vinyals , Wojciech Zaremba
CPC classification number: G06F17/2881 , G06F7/023 , G06F7/10 , G06F17/2735 , G06F17/2818 , G06F17/2827 , G06N3/0445 , G06N3/0454 , G10L15/02 , G10L15/16
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for neural translation systems with rare word processing. One of the methods is a method training a neural network translation system to track the source in source sentences of unknown words in target sentences, in a source language and a target language, respectively and includes deriving alignment data from a parallel corpus, the alignment data identifying, in each pair of source and target language sentences in the parallel corpus, aligned source and target words; annotating the sentences in the parallel corpus according to the alignment data and a rare word model to generate a training dataset of paired source and target language sentences; and training a neural network translation model on the training dataset.
Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于具有罕见文字处理的神经翻译系统。 其中一种方法是训练神经网络翻译系统，以分别在源语言和目标语言中跟踪目标语句中的未知单词的源语句中的源，并且包括从并行语料库导出对齐数据，对齐数据 在平行语料库中的每对源和目标语言句子中识别对齐的源词和目标词; 根据对齐数据和平行语料库中的句子注释罕见词模型，以生成配对的源语言和目标语言句子的训练数据集; 并在训练数据集上训练神经网络翻译模型。
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公开(公告)号：US20200293873A1
公开(公告)日：2020-09-17
申请号：US15262959
申请日：2016-09-12
Applicant: Google Inc.
Inventor： Andrew M. Dai , Quoc V. Le , Gregory Sean Corrado
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating document vector representations. One of the methods includes obtaining a new document; selecting a plurality of new document word sets; and determining a vector representation for the new document using a trained neural network system, wherein the trained neural network system comprises: a document embedding layer and a classifier, and wherein determining the vector representation for the new document using the trained neural network system comprises iteratively providing each of the plurality of new document word sets to the trained neural network system to determine the vector representation for the new document using gradient descent.
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公开(公告)号：US20170140265A1
公开(公告)日：2017-05-18
申请号：US15349955
申请日：2016-11-11
Applicant: Google Inc.
Inventor： Quoc V. Le , Ilya Sutskever , Arvind Neelakantan
CPC classification number: G06N3/0445 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing operations using data from a data source. In one aspect, a method includes a neural network system including a controller neural network configured to: receive a controller input for a time step and process the controller input and a representation of a system input to generate: an operation score distribution that assigns a respective operation score to an operation and a data score distribution that assigns a respective data score in the data source. The neural network system can also include an operation subsystem configured to: perform operations to generate operation outputs, wherein at least one of the operations is performed on data in the data source, and combine the operation outputs in accordance with the operation score distribution and the data score distribution to generate a time step output for the time step.
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