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SYSTEM AND METHOD FOR TRAINING A DAMAGE IDENTIFICATION MODEL

机译:训练损伤识别模型的系统和方法

摘要

A system is provided for identifying damages of a vehicle. During operation, the system can obtain a set of digital images associated with a set of tagged digital images as training data. Each tagged digital image in the set of tagged digital images may include at least one damage object. The system can train a damage identification model based on the training data. When training the damage identification model, the system may identify at least a damage object in the training data based on a target detection technique. The system may also generate a set of feature vectors for the training data. The system can use the set of feature vectors to optimize a set of parameters associated with the damage identification model to obtain a trained damage identification model. The system can then apply the trained damage identification model to obtain a damage category prediction result
机译:提供了一种用于识别车辆损坏的系统。在操作期间,系统可以获得与一组标记的数字图像相关联的一组数字图像作为训练数据。一组标记的数字图像中的每个标记的数字图像可以包括至少一个损坏对象。该系统可以基于训练数据来训练损伤识别模型。当训练伤害识别模型时,系统可以基于目标检测技术在训练数据中至少识别伤害对象。系统还可以为训练数据生成一组特征向量。该系统可以使用该组特征向量来优化与损伤识别模型相关联的一组参数,以获得训练后的损伤识别模型。然后,系统可以应用经过训练的损害识别模型来获得损害类别预测结果

著录项

  • 公开/公告号US2020090320A1

    专利类型

  • 公开/公告日2020-03-19

    原文格式PDF

  • 申请/专利权人 ALIBABA GROUP HOLDING LIMITED;

    申请/专利号US201916554223

  • 发明设计人 JUAN XU;

    申请日2019-08-28

  • 分类号G06T7;G06F16/58;G06N20;G06N5/04;G06K9/62;

  • 国家 US

  • 入库时间 2022-08-21 11:23:10

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