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System and method for procedurally synthesizing datasets of objects of interest for training machine-learning models

机译:用于训练机器学习模型的过程化感兴趣对象数据集的系统和方法

摘要

A system and method for procedurally synthesizing a training dataset for training a machine-learning model. In one embodiment, the system includes: (1) a training designer configured to describe variations in content of training images to be included in the training dataset and (2) an image definer coupled to the training designer, configured to generate training image definitions in accordance with the variations and transmit the training image definitions: to a 3D graphics engine for rendering into corresponding training images, and further to a ground truth generator for generating associated ground truth corresponding to the training images, the training images and the associated ground truth comprising the training dataset.
机译:一种用于过程地合成用于训练机器学习模型的训练数据集的系统和方法。在一个实施例中,该系统包括:(1)训练设计器,其被配置为描述要包括在训练数据集中的训练图像的内容的变化;(2)与训练设计器耦合的图像定义器,其被配置为生成训练图像定义根据变化并传送训练图像定义:到3D图形引擎以渲染成相应的训练图像,并且进一步到地面事实发生器,用于生成与训练图像相对应的相关地面事实,训练图像和相关地面事实包括:训练数据集。

著录项

  • 公开/公告号US10643106B2

    专利类型

  • 公开/公告日2020-05-05

    原文格式PDF

  • 申请/专利权人 NVIDIA CORPORATION;

    申请/专利号US201815979547

  • 发明设计人 JESSE CLAYTON;VLADIMIR GLAVTCHEV;

    申请日2018-05-15

  • 分类号G06K9/62;G06K9;G06T15;G06K9/66;G06N5/04;G06N20;

  • 国家 US

  • 入库时间 2022-08-21 11:26:40

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