公开(公告)号：US12159366B2

公开(公告)日：2024-12-03

申请号：US17436298

申请日：2020-03-12

Applicant: GOOGLE LLC

Inventor： Adam Prins ,  Erin Hoffman-John ,  Ryan Poplin ,  Richard Wu ,  Andeep Toor

IPC: G06T3/40 ,  G06T5/00 ,  G06T5/50

Abstract: Systems and methods are provided for receiving at least one image and a reference image, and performing a plurality of downscaling operations having separable convolutions on the received at least one image. A plurality of residual blocks may be formed, with each residual block containing two separable convolutions of the kernel and two instance normalizations. A plurality of upscaling operations may be performed on the plurality of residual blocks, and a stylized image may be displayed based on at least the performed plurality of upscaling operations and the reference image.

公开(公告)号：US11636601B2

公开(公告)日：2023-04-25

申请号：US17212811

申请日：2021-03-25

Applicant: GOOGLE LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G16H50/30 ,  G16H50/20 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

公开(公告)号：US20230215083A1

公开(公告)日：2023-07-06

申请号：US17928874

申请日：2020-06-04

Applicant: GOOGLE LLC

Inventor： Erin Hoffman-John ,  Ryan Poplin ,  Andeep Singh Toor ,  William Lee Dotson ,  Trung Tuan Lee

IPC: G06T15/20 ,  G06T15/50 ,  G06T15/04

CPC classification number: G06T15/205 ,  G06T15/50 ,  G06T15/04

Abstract: A virtual camera captures first images of a three-dimensional (3D) digital representation of a visual asset from different perspectives and under different lighting conditions. The first images are training images that are stored in a memory. One or more processors implement a generative adversarial network (GAN) that includes a generator and a discriminator, which are implemented as different neural networks. The generator generates second images that represent variations of the visual asset concurrently with the discriminator attempting to distinguish between the first and second images. The one or more processors update a first model in the discriminator and/or a second model in the generator based on whether the discriminator successfully distinguished between the first and second images. Once trained, the generator generates images of the visual asset based on the first model, e.g., based on a label or an outline of the visual asset.

公开(公告)号：US20230260126A1

公开(公告)日：2023-08-17

申请号：US18305789

申请日：2023-04-24

Applicant: Google LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G16H50/30 ,  G16H50/20 ,  G06N3/044 ,  G06N3/08

CPC classification number: G06T7/0016 ,  G16H50/30 ,  G16H50/20 ,  G06N3/044 ,  G06N3/08 ,  G01N2800/168 ,  G01N2800/164 ,  G06T2207/10016 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30041

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

公开(公告)号：US20210209762A1

公开(公告)日：2021-07-08

申请号：US17212811

申请日：2021-03-25

Applicant: GOOGLE LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G16H50/30 ,  G16H50/20 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

公开(公告)号：US20190180441A1

公开(公告)日：2019-06-13

申请号：US16325580

申请日：2017-08-18

Applicant: GOOGLE LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G06N3/04 ,  G06N3/08 ,  G16H50/20 ,  G16H50/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

公开(公告)号：US20220253747A1

公开(公告)日：2022-08-11

申请号：US17616494

申请日：2020-05-26

Applicant: Google LLC

Inventor： Jie Ren ,  Balaji Lakshminarayanan ,  Peter Junteng Liu ,  Joshua Vincent Dillon ,  Roland Jasper Snoek ,  Ryan Poplin ,  Mark Andrew DePristo ,  Emily Amanda Fertig

IPC: G06N20/00 ,  G06N3/12

Abstract: The present disclosure is directed to systems and method to perform improved detection of out-of-distribution (OOD) inputs. In particular, current deep generative model-based approaches for OOD detection are significantly negatively affected by and struggle to distinguish population level background statistics from semantic content relevant to the in-distribution examples. In fact, such approaches have even been experimentally observed to assign higher likelihood to OOD inputs, which is opposite to the desired behavior. To resolve this problem, the present disclosure proposes a likelihood ratio method for deep generative models which effectively corrects for these confounding background statistics.

公开(公告)号：US10970841B2

公开(公告)日：2021-04-06

申请号：US16325580

申请日：2017-08-18

Applicant: GOOGLE LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G16H50/30 ,  G16H50/20 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.