公开(公告)号：US20220035684A1

公开(公告)日：2022-02-03

申请号：US17330710

申请日：2021-05-26

Applicant: NVIDIA Corporation

Inventor： Shaunak Gupte ,  Amit Kale ,  Bhushan Rupde ,  Kaustubh Purandare

IPC: G06F9/50 ,  G06F9/30 ,  G06N3/04

Abstract: Apparatuses, systems, and techniques to balance processing load between a plurality of hardware accelerators. In at least one embodiment, operations performed on batches of frames of a video (e.g., as part of a video analytics pipeline) are distributed by a load balancer between a first hardware accelerator and a second hardware accelerator.

公开(公告)号：US20230139682A1

公开(公告)日：2023-05-04

申请号：US17516506

申请日：2021-11-01

Applicant: NVIDIA Corporation

Inventor： Amit Kale ,  Bhushan Rupde ,  Kaustubh Purandare

IPC: G06K9/62 ,  G06K9/00 ,  G06T5/00 ,  G06N3/04

Abstract: Apparatuses, systems, and techniques for continuous training of an object detection and/or classification model. A first image including a depiction of an environment based on a first set of conditions is identified. Object data associated with an object detected in the first image is obtained based on one or more outputs of a machine learning model. A determination is made of whether a level of confidence that an object corresponds to an object class satisfies a level of confidence criterion. If so, a first set of conditions corresponding to the environment depicted in the first image. One or more noise characteristics associated with a second image including a depiction of the environment is determined based on a difference between the first set of conditions and a second set of conditions of the second image. The first image is augmented based on the one or more determined noise characteristics to generate a third image. The third image reflects the depiction of the environment based on the second set of conditions and a depiction of the object detected in the first image. Training data is associated with the third image is provided to train the machine learning model.