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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
Applicant: Nvidia Corporation
Inventor： Andriy Myronenko , Ziyue Xu , Dong Yang , Holger Roth , Daguang Xu
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.
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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
Applicant: Nvidia Corporation
Inventor： Dong Yang , Andriy Myronenko , Xiaosong Wang , Ziyue Xu , Holger Roth , Daguang Xu
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.
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公开(公告)号：US20220284582A1
公开(公告)日：2022-09-08
申请号：US17190724
申请日：2021-03-03
Applicant: NVIDIA Corporation
Inventor： Dong Yang , Yufan He , Holger Reinhard Roth , Can Zhao , Daguang Xu
Abstract: Apparatuses, systems, and techniques to select a neural network using an amount of memory to be used. In at least one embodiment, a processor includes one or more circuits to cause one or more neural networks to be selected from a plurality of neural networks based, at least in part, on an amount of memory to be used by the one oe more neural networks.
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公开(公告)号：US20210397943A1
公开(公告)日：2021-12-23
申请号：US16905252
申请日：2020-06-18
Applicant: NVIDIA Corporation
Inventor： Pablo Ribalta , Michal Marcinkiewicz , Dong Yang , Daguang Xu , Przemyslaw Miroslaw Strzelczyk
Abstract: Apparatuses, systems, and techniques to train neural networks to perform classification. In at least one embodiment, one or more neural networks are trained to perform classification based on, for example, using one or more compressed representations of one or more class labels, where the one or more compressed representations have fewer bits than a representation of the one or more class labels.
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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
Applicant: NVIDIA Corporation
Inventor： Holger Reinhard Roth , Dong Yang , Wenqi Li , Andriy Myronenko , Wentao Zhu , Ziyue Xu , Xiaosong Wang , Daguang Xu
Abstract: 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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Patent Agency Ranking
公开(公告)号：US20200293828A1
公开(公告)日：2020-09-17
申请号：US16813673
申请日：2020-03-09
Applicant: NVIDIA Corporation
Inventor： Xiaosong Wang , Ziyue Xu , Dong Yang , Holger Reinhard Roth , Andriy Myronenko , Daguang Xu , Ling Zhang
Abstract: 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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公开(公告)号：US20240303504A1
公开(公告)日：2024-09-12
申请号：US18124999
申请日：2023-03-22
Applicant: NVIDIA Corporation
Inventor： Ziyue Xu , Holger Reinhard Roth , Meirui Jiang , Wenqi Li , Dong Yang , Can Zhao , Vishwesh Nath , Daguang Xu
IPC: G06N3/098
CPC classification number: G06N3/098
Abstract: Apparatuses, systems, and techniques to train/use one or more neural networks. In at least one embodiment, a processor comprises one or more circuits to cause neural network training information to be aggregated based, at least in part, on contribution of the neural network training data and one or more performance metrics of the neural network.
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公开(公告)号：US20220058466A1
公开(公告)日：2022-02-24
申请号：US16998694
申请日：2020-08-20
Applicant: NVIDIA Corporation
Inventor： Dong Yang , Wenqi Li , Ziyue Xu , Xiaosong Wang , Can Zhao , Holger Reinhard Roth , Daguang Xu
Abstract: Apparatuses, systems, and techniques to generate an optimized neural network architecture. In at least one embodiment, various neural network components are used to generate one or more neural network configurations, and each neural network configuration is trained in order to determine an optimal neural network architecture for a training dataset.
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公开(公告)号：US20220027672A1
公开(公告)日：2022-01-27
申请号：US16940241
申请日：2020-07-27
Applicant: NVIDIA Corporation
Inventor： Ziyue Xu , Xiaosong Wang , Dong Yang , Holger Reinhard Roth , Can Zhao , Wentao Zhu , Daguang Xu
Abstract: Apparatuses, systems, and techniques to train one or more neural networks to generate labels for unsupervised or partially-supervised data. In at least one embodiment, one or more pseudolabels are generated by a training framework based on available weak annotations for an input medical image, and combined with feature information about said input medical image generated by one or more neural networks to generate a label about said input medical image.
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公开(公告)号：US20210334955A1
公开(公告)日：2021-10-28
申请号：US16858219
申请日：2020-04-24
Applicant: Nvidia Corporation
Inventor： Holger Roth , Dong Yang , Daguang Xu , Vishwesh Nath
IPC: G06T7/00 , G06F40/169 , G06N3/08 , G06T7/11
Abstract: Apparatuses, systems, and techniques are presented to predict annotations for objects in images. In at least one embodiment, one or more annotations corresponding to one or more objects within one or more images are generated based, at least in part, on one or more neural networks iteratively trained using the one or more images.
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