首页> 外国专利> A METHOD AND SYSTEM FOR TRAINING A MACHINE LEARNING MODEL FOR CLASSIFICATION OF COMPONENTS IN A MATERIAL STREAM

A METHOD AND SYSTEM FOR TRAINING A MACHINE LEARNING MODEL FOR CLASSIFICATION OF COMPONENTS IN A MATERIAL STREAM

机译:一种用于训练机器学习模型的方法和系统,用于在材料流中分类组件的分类

摘要

A method and system for training a machine learning model configured to perform characterization of components in a material stream with a plurality of unknown components. A training reward associated with each unknown component within the plurality of unknown components in the material stream is determined, based on which at least one unknown component is physically isolated from the material stream by means of a separator unit, wherein the separator unit is configured to move the selected unknown component to a separate accessible compartment. The isolated at least one unknown component is analyzed for determining the ground truth label thereof, wherein the determined ground truth is used for training an incremental version of the machine learning model.
机译:用于训练机器学习模型的方法和系统,其被配置为在具有多个未知组件的材料流中执行组件的表征。 确定与材料流中的多个未知组件内的每个未知组件相关联的训练奖励,基于该未知组件通过分离单元从材料流物理隔离,其中分离器单元配置为 将所选未知组件移动到单独的可访问隔间。 分析孤立的至少一个未知组件以确定其地面真实标签,其中所确定的基础事实用于训练机器学习模型的增量版本。

著录项

  • 公开/公告号EP3896602A1

    专利类型

  • 公开/公告日2021-10-20

    原文格式PDF

  • 申请/专利权人 VITO NV;

    申请/专利号EP20200169824

  • 发明设计人 GEURTS ROELAND;

    申请日2020-04-16

  • 分类号G06K9;G06K9/62;B07C5;B09B3;

  • 国家 EP

  • 入库时间 2022-08-24 21:46:59

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