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公开(公告)号:US20240330682A1
公开(公告)日:2024-10-03
申请号:US18295094
申请日:2023-04-03
Applicant: Adobe Inc.
Inventor: Surgan JANDIAL , Siddarth Ramesh , Piyush Gupta , Gauri Gupta , Balaji Krishnamurthy
IPC: G06N3/08 , G06N3/0455
CPC classification number: G06N3/08 , G06N3/0455
Abstract: Systems and methods for generating synthetic tabular data for machine learning and other applications are provided. In some embodiments, a variational autoencoder is trained to learn inter-feature correlations found in tabular data collected from real data sources. The trained variational autoencoder is used to train a generator model of a Generative Adversarial Network (GAN) to generate synthetic tabular data that exhibits the inter-feature correlation distribution found in the tabular data collected from real data sources. In some embodiments, processing devices perform operations comprising: receiving a set of tabular data records, each record comprising a plurality of features; training a first machine learning model using the tabular data records to learn correlations between the plurality of features; and training a second machine learning model, using the first machine learning model, to generate a synthetic tabular data records based at least on the one or more correlations between the plurality of features.
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公开(公告)号:US20240070816A1
公开(公告)日:2024-02-29
申请号:US17823582
申请日:2022-08-31
Applicant: ADOBE INC.
Inventor: Surgan Jandial , Siddarth Ramesh , Shripad Vilasrao Deshmukh , Balaji Krishnamurthy
IPC: G06T5/50 , G06T5/00 , G06V10/74 , G06V10/764 , G06V10/774 , G06V20/70
CPC classification number: G06T5/50 , G06T5/002 , G06V10/761 , G06V10/764 , G06V10/774 , G06V20/70 , G06T2207/20081 , G06T2207/20084
Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure receive a reference image depicting a reference object with a target spatial attribute; generate object saliency noise based on the reference image by updating random noise to resemble the reference image; and generate an output image based on the object saliency noise, wherein the output image depicts an output object with the target spatial attribute.
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