公开(公告)号：US20240104345A1

公开(公告)日：2024-03-28

申请号：US17859670

申请日：2022-07-07

Applicant: Nvidia Corporation

Inventor： Cheng Peng ,  Andriy Myronenko ,  Ali Hatamizsadeh ,  Vishwesh Nath ,  Md Mahfuzur Rahman Siddiquee ,  Yufan He ,  Daguang Xu ,  Dong Yang

IPC: G06N3/04 ,  G06N3/08 ,  G16H30/20

CPC classification number: G06N3/0454 ,  G06N3/08 ,  G16H30/20

Abstract: Apparatuses, systems, and techniques are presented to generate images representing realistic motion or activity. In at least one embodiment, one or more neural networks are used to select a first neural network to perform a first task based, at least in part, upon a performance estimated by a second neural network.

公开(公告)号：US11816185B1

公开(公告)日：2023-11-14

申请号：US16383347

申请日：2019-04-12

Applicant: Nvidia Corporation

Inventor： Holger Roth ,  Yingda Xia ,  Dong Yang ,  Daguang Xu

IPC: G06F18/214 ,  G06F9/30 ,  G06N3/08 ,  G16H30/40 ,  G06N5/04 ,  G06F18/211 ,  G06F18/2433 ,  G06N3/045

CPC classification number: G06F18/2155 ,  G06F9/3001 ,  G06F18/211 ,  G06F18/2433 ,  G06N3/045 ,  G06N3/08 ,  G06N5/04 ,  G16H30/40 ,  G06V2201/031

Abstract: Volumetric quantification can be performed for various parameters of an object represented in volumetric data. Multiple views of the object can be generated, and those views provided to a set of neural networks that can generate inferences in parallel. The inferences from the different networks can be used to generate pseudo-labels for the data, for comparison purposes, which enables a co-training loss to be determined for the unlabeled data. The co-training loss can then be used to update the relevant network parameters for the overall data analysis network. If supervised data is also available then the network parameters can further be updated using the supervised loss.

公开(公告)号：US20230145535A1

公开(公告)日：2023-05-11

申请号：US17188338

申请日：2021-03-01

Applicant: NVIDIA Corporation

Inventor： Ali Hatamizadeh ,  Daguang Xu ,  Xiaosong Wang ,  Lickkong Tam ,  Riddhish Bhalodia

IPC: G16H50/20 ,  G16H30/40 ,  G06T7/00 ,  G06T7/11

CPC classification number: G16H50/20 ,  G16H30/40 ,  G06T7/0012 ,  G06T7/11

Abstract: Apparatuses, systems, and techniques to train a neural network to infer a condition based on an image. In at least one embodiment, a first portion of a neural network is trained to infer a condition from an image using a first dataset, and a second portion of the neural network is trained using a second dataset.

公开(公告)号：US20220101113A1

公开(公告)日：2022-03-31

申请号：US17033439

申请日：2020-09-25

Applicant: NVIDIA Corporation

Inventor： Lickkong Tam ,  Xiaosong Wang ,  Daguang Xu

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  G06F40/263 ,  G06F40/284 ,  G16H70/40

Abstract: Apparatuses, systems, and techniques to identify one or more relationships among one or more words using one or more transformer-based language neural networks trained using domain-specific data.

公开(公告)号：US20220076133A1

公开(公告)日：2022-03-10

申请号：US17013432

申请日：2020-09-04

Applicant: NVIDIA Corporation

Inventor： Dong Yang ,  Ziyue Xu ,  Wenqi Li ,  Andriy Myronenko ,  Holger Reinhard Roth ,  Xiaosong Wang ,  Wentao Zhu ,  Daguang Xu

IPC: G06N3/08 ,  G06N3/04

Abstract: Apparatuses, systems, and techniques to facilitate global semi-supervised training of neural networks to perform image segmentation related to diagnosis and management of emerging diseases, such as COVID-19. In at least one embodiment, distributed client training frameworks train one or more client neural networks to perform image segmentation according to a local training data set as well as global neural network data aggregated, by one or more central servers, from each of one or more globally distributed client neural networks.

公开(公告)号：US20210049757A1

公开(公告)日：2021-02-18

申请号：US16540717

申请日：2019-08-14

Applicant: NVIDIA Corporation

Inventor： Wentao Zhu ,  Daguang Xu ,  Andriy Myronenko ,  Ziyue Xu

IPC: G06T7/00 ,  G06T7/33 ,  G06T7/11 ,  G06N3/08 ,  G06F17/50

Abstract: Apparatuses, systems, and techniques to perform registration among images. In at least one embodiment, one or more neural networks are trained to indicate registration of features in common among at least two images by generating a first correspondence by simulating a registration process of registering an image and applying the at least two images and the first correspondence to a neural network to derive a second correspondence of the features in common among the at least two images.

公开(公告)号：US20240161281A1

公开(公告)日：2024-05-16

申请号：US18405922

申请日：2024-01-05

Applicant: NVIDIA Corporation

Inventor： Wentao Zhu ,  Daguang Xu ,  Andriy Myronenko ,  Ziyue Xu

IPC: G06T7/00 ,  G06F30/20 ,  G06N3/08 ,  G06T7/11 ,  G06T7/33

CPC classification number: G06T7/0012 ,  G06F30/20 ,  G06N3/08 ,  G06T7/11 ,  G06T7/344 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Apparatuses, systems, and techniques to perform registration among images. In at least one embodiment, one or more neural networks are trained to indicate registration of features in common among at least two images by generating a first correspondence by simulating a registration process of registering an image and applying the at least two images and the first correspondence to a neural network to derive a second correspondence of the features in common among the at least two images.

公开(公告)号：US11804050B1

公开(公告)日：2023-10-31

申请号：US16671001

申请日：2019-10-31

Applicant: NVIDIA Corporation

Inventor： Fausto Milletari ,  Maximilian Baust ,  Nicola Rieke ,  Wenqi Li ,  Daguang Xu ,  Andrew Feng ,  Rong Ou ,  Yan Cheng

IPC: G06V20/64 ,  G06N3/063 ,  G06N3/08 ,  G06N3/045

CPC classification number: G06V20/64 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08

Abstract: Apparatuses, systems, and techniques to collaboratively train one or more machine learning models. Parameter reviewers may be configured to compare sets of machine learning model parameter information in order to generate one or more machine learning models, such as neural networks.

公开(公告)号：US20230069310A1

公开(公告)日：2023-03-02

申请号：US17398655

申请日：2021-08-10

Applicant: Nvidia Corporation

Inventor： Andriy Myronenko ,  Ziyue Xu ,  Dong Yang ,  Holger Roth ,  Daguang Xu

IPC: G06T7/11 ,  G06K9/62 ,  G06N3/08

Abstract: Apparatuses, systems, and techniques are presented to classify objects in images. In at least one embodiment, one or more neural networks are used to identify one or more objects in one or more full images based, at least in part, on the one or more neural networks having been trained using the one or more full images and one or more portions of the one or more full images.

公开(公告)号：US20230061998A1

公开(公告)日：2023-03-02

申请号：US17459644

申请日：2021-08-27

Applicant: Nvidia Corporation

Inventor： Dong Yang ,  Andriy Myronenko ,  Xiaosong Wang ,  Ziyue Xu ,  Holger Roth ,  Daguang Xu

IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06F7/24

Abstract: Apparatuses, systems, and techniques are presented to select neural networks. In at least one embodiment, one or more first neural networks can be used to select one or more second neural networks, as may be based at least in part upon an inference to be generated by the one or more second neural networks.