公开(公告)号：US20250061323A1

公开(公告)日：2025-02-20

申请号：US18367223

申请日：2023-09-12

Applicant: NVIDIA Corporation

Inventor： Vishwesh Nath ,  Daguang Xu ,  Bin Liu ,  Yufan He ,  Sachidanand Alle ,  Pengcheng Ma ,  Raghav Mani ,  Marc Thomas Edgar ,  Andrew Feng

IPC: G06N3/08

Abstract: Apparatuses, systems, and techniques to perform active learning. In at least one embodiment, one or more neural networks are trained using training data selected for manual relabeling based, at least in part, on an amount by which the training data is mis-labeled

公开(公告)号：US20240185100A1

公开(公告)日：2024-06-06

申请号：US18076221

申请日：2022-12-06

Applicant: NVIDIA Corporation

Inventor： Alvin Ihsani ,  Shaul Arazi ,  Elena Agostini ,  Penn Tasinga ,  Carl Everett Lacey, JR. ,  Dana Groff ,  Dotan David Levi ,  Wojciech Wasko ,  Vishwesh Nath ,  Sachidanand Alle

IPC: G06N5/04 ,  G16H30/20

CPC classification number: G06N5/04 ,  G16H30/20

Abstract: Methods and systems for obtaining data having a first format, converting the data to a second format, storing the converted data in memory accessible by at least one parallel processing unit, and processing the converted data stored in the memory using the at least one parallel processing unit.

公开(公告)号：US20200027210A1

公开(公告)日：2020-01-23

申请号：US16515890

申请日：2019-07-18

Applicant: NVIDIA Corporation

Inventor： Nicholas Haemel ,  Bojan Vukojevic ,  Risto Haukioja ,  Andrew Feng ,  Yan Cheng ,  Sachidanand Alle ,  Daguang Xu ,  Holger Reinhard Roth ,  Johnny Israeli

IPC: G06T7/00 ,  G16H30/20 ,  G06T19/00 ,  G06N5/04 ,  G06N3/04 ,  G06T7/10 ,  G06F9/455 ,  G06F9/54 ,  G06T5/00

Abstract: In various examples, a virtualized computing platform for advanced computing operations—including image reconstruction, segmentation, processing, analysis, visualization, and deep learning—may be provided. The platform may allow for inference pipeline customization by selecting, organizing, and adapting constructs of task containers for local, on-premises implementation. Within the task containers, machine learning models generated off-premises may be leveraged and updated for location specific implementation to perform image processing operations. As a result, and using the virtualized computing platform, facilities such as hospitals and clinics may more seamlessly train, deploy, and integrate machine learning models within a production environment for providing informative and actionable medical information to practitioners.