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公开(公告)号：US20220076133A1
公开(公告)日：2022-03-10
申请号：US17013432
申请日：2020-09-04
申请人： NVIDIA Corporation
发明人： Dong Yang , Ziyue Xu , Wenqi Li , Andriy Myronenko , Holger Reinhard Roth , Xiaosong Wang , Wentao Zhu , Daguang Xu
摘要： 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.
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2.发明申请公开(公告)号：US20210049757A1
公开(公告)日：2021-02-18
申请号：US16540717
申请日：2019-08-14
申请人： NVIDIA Corporation
发明人： Wentao Zhu , Daguang Xu , Andriy Myronenko , Ziyue Xu
摘要： 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.
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3.发明公开公开(公告)号：US20240161282A1
公开(公告)日：2024-05-16
申请号：US18405932
申请日：2024-01-05
申请人： NVIDIA Corporation
发明人： Wentao Zhu , Daguang Xu , Andriy Myronenko , Ziyue Xu
CPC分类号： G06T7/0012 , G06F30/20 , G06N3/08 , G06T7/11 , G06T7/344 , G06T2207/20081 , G06T2207/20084
摘要： 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.
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公开(公告)号：US20230021926A1
公开(公告)日：2023-01-26
申请号：US17373309
申请日：2021-07-12
申请人： NVIDIA Corporation
发明人： Can Zhao , Daguang Xu , Holger Reinhard Roth , Ziyue Xu , Dong Yang , Andriy Myronenko , Lickkong Tam
摘要： Apparatuses, systems, and techniques to generate one or more images of an object. In at least one embodiment, a technique includes training one or more neural networks to generate one or more images of an object from at least a first image of the object and a second lower-resolution image of the object, where the training includes a comparison of the one or more generated images of the object with the second lower-resolution image of the object.
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公开(公告)号：US20230019211A1
公开(公告)日：2023-01-19
申请号：US17364341
申请日：2021-06-30
申请人： NVIDIA Corporation
发明人： Xiaosong Wang , Ziyue Xu , Lickkong Tam , Dong Yang , Daguang Xu
摘要： Apparatuses, systems, and techniques to indicate an extent, to which text corresponds to one or more images. In at least one embodiment, an extent to which text corresponds to one or more images is indicated using one or more neural networks and used to train the one or more neural networks.
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6.发明公开公开(公告)号：US20240161281A1
公开(公告)日：2024-05-16
申请号：US18405922
申请日：2024-01-05
申请人： NVIDIA Corporation
发明人： Wentao Zhu , Daguang Xu , Andriy Myronenko , Ziyue Xu
CPC分类号： G06T7/0012 , G06F30/20 , G06N3/08 , G06T7/11 , G06T7/344 , G06T2207/20081 , G06T2207/20084
摘要： 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.
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公开(公告)号：US20230069310A1
公开(公告)日：2023-03-02
申请号：US17398655
申请日：2021-08-10
申请人： Nvidia Corporation
发明人： Andriy Myronenko , Ziyue Xu , Dong Yang , Holger Roth , Daguang Xu
摘要： 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.
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公开(公告)号：US20230061998A1
公开(公告)日：2023-03-02
申请号：US17459644
申请日：2021-08-27
申请人： Nvidia Corporation
发明人： Dong Yang , Andriy Myronenko , Xiaosong Wang , Ziyue Xu , Holger Roth , Daguang Xu
摘要： 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.
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公开(公告)号：US20210374502A1
公开(公告)日：2021-12-02
申请号：US16889652
申请日：2020-06-01
申请人： NVIDIA Corporation
发明人： Holger Reinhard Roth , Dong Yang , Wenqi Li , Andriy Myronenko , Wentao Zhu , Ziyue Xu , Xiaosong Wang , Daguang Xu
摘要： Apparatuses, systems, and techniques to select a nueral network architecture from a plurality of neural networs in a federated learning (FL) settng. In at least one embodiment, a neural network is trained by combining training resutls from different FL computing systesms, where each of the different FL computing systems, for example, trains different portions of the nerual network.
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公开(公告)号：US20200293828A1
公开(公告)日：2020-09-17
申请号：US16813673
申请日：2020-03-09
申请人： NVIDIA Corporation
发明人： Xiaosong Wang , Ziyue Xu , Dong Yang , Holger Reinhard Roth , Andriy Myronenko , Daguang Xu , Ling Zhang
摘要： Apparatuses, systems, and techniques to perform training of neural networks using stacked transformed images. In at least one embodiment, a neural network is trained on stacked transformed images and trained neural network is provided to be used for processing images from an unseen domain distinct from a source domain, wherein stacked transformed images are transformed according to transformation aspects related to domain variations.
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