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公开(公告)号：US11087504B2
公开(公告)日：2021-08-10
申请号：US16494386
申请日：2018-05-21
Applicant: Google LLC
Inventor： Sergio Guadarrama Cotado , Jonathon Shlens , David Bieber , Mohammad Norouzi , Kevin Patrick Murphy , Ryan Lienhart Dahl
Abstract: Systems and methods for transforming grayscale images into color images using deep neural networks are described. One of the systems include one or more computers and one or more storage devices storing instructions that, when executed by one or more computers, cause the one or more computers to implement a coloring neural network, a refinement neural network, and a subsystem. The coloring neural network is configured to receive a first grayscale image having a first resolution and to process the first grayscale image to generate a first color image having a second resolution lower than the first resolution. The subsystem processes the first color image to generate a set of intermediate image outputs. The refinement neural network is configured to receive the set intermediate image outputs, and to process the set of intermediate image outputs to generate a second color image having a third resolution higher than the second resolution.
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公开(公告)号：US20200098144A1
公开(公告)日：2020-03-26
申请号：US16494386
申请日：2018-05-21
Applicant: Google LLC
Inventor： Mohammad Norouzi , Jonathon Shiens , David Bieber , Sergio Guadarrama Cotado , Kevin Patrick Murphy , Ryan Lienhart Dahl
Abstract: Systems and methods for transforming grayscale images into color images using deep neural networks are described. One of the systems include one or more computers and one or more storage devices storing instructions that, when executed by one or more computers, cause the one or more computers to implement a coloring neural network, a refinement neural network, and a subsystem. The coloring neural network is configured to receive a first grayscale image having a first resolution and to process the first grayscale image to generate a first color image having a second resolution lower than the first resolution. The subsystem processes the first color image to generate a set of intermediate image outputs. The refinement neural network is configured to receive the set intermediate image outputs, and to process the set of intermediate image outputs to generate a second color image having a third resolution higher than the second resolution.
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公开(公告)号：US20240273270A1
公开(公告)日：2024-08-15
申请号：US18564797
申请日：2022-05-31
Applicant: Google LLC
Inventor： Shobha Vasudevan , Wenjie Jiang , Charles Aloysius Sutton , Rishabh Singh , David Bieber , Milad Olia Hashemi , Chian-min Richard Ho , Hamid Shojaei
IPC: G06F30/323 , G06F30/33
CPC classification number: G06F30/323 , G06F30/33
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating learned representations of digital circuit designs. One of the systems includes obtaining data representing a program that implements a digital circuit design, the program comprising a plurality of statements; processing the obtained data to generate data representing a graph representing the digital circuit design, the graph comprising: a plurality of nodes representing respective statements of the program, a plurality of first edges each representing a control flow between a pair of statements of the program, and a plurality of second edges each representing a data flow between a pair of statements of the program; and generating a learned representation of the digital circuit design, comprising processing the data representing the graph using a graph neural network to generate a respective learned representation of each statement represented by a node of the graph.
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