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METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO RECONSTRUCT SCENES USING CONVOLUTIONAL NEURAL NETWORKS

机译:使用卷积神经网络重建场景的方法,系统,制品和装置

摘要

Methods, apparatus, systems and articles of manufacture to reconstruct scenes using convolutional neural networks are disclosed. An example apparatus includes a sensor data acquirer to acquire ground truth data representing an environment, an environment detector to identify an environmental characteristic of the environment, a synthetic database builder to apply noise to the ground truth data to form a training set, a model builder to train a machine learning model using the training set and the ground truth data, and a model adjustor to modify the machine learning model to include residual OR-gate connections intermediate respective layers of the machine learning model. The synthetic database builder is further to store the machine learning model in association with the environmental characteristic of the environment.
机译:公开了使用卷积神经网络重建场景的制造方法,装置,系统和制品。示例装置包括传感器数据获取器,用于获取表示环境的地面真理数据,一个环境检测器要识别环境的环境特征,一个合成数据库构建器,用于将噪声应用于地面真理数据,以形成培训集,模型构建器要使用训练集和地面真实数据训练机器学习模型,以及模型调节器来修改机器学习模型,包括剩余或栅极连接中间相应的机器学习模型层。合成数据库构建器进一步存储与环境的环境特征相关联的机器学习模型。

著录项

  • 公开/公告号US2021073640A1

    专利类型

  • 公开/公告日2021-03-11

    原文格式PDF

  • 申请/专利权人 MOVIDIUS LTD.;

    申请/专利号US202017100531

  • 申请日2020-11-20

  • 分类号G06N3/08;G06N3/04;G06N3/063;G06N5/02;G06K9/62;

  • 国家 US

  • 入库时间 2022-08-24 17:38:18

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