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TRAINING FOR ARTIFICIAL NEURAL NETWORKS WITH BETTER UTILIZATION OF LEARNING DATA RECORDS

机译:更好地利用学习数据记录进行人工神经网络训练

摘要

A method (100) for training an artificial neural network, ANN (1), with learning data records (2) that each comprise a sample (11a) and an associated label (12a), wherein each sample (11a) represents values of one or more input variables (11) of the ANN (1) and the associated label (12a) represents values of one or more output variables (12) of the ANN (1), having the steps of: - the ANN (1) is trained (110) in unmonitored fashion on the basis of the samples (11a) contained in the learning data records (2); - at least one quality criterion (3) for the reliability and/or quality of the association of labels (12a) with samples (11a) in the learning data records (2) is taken as a basis for determining (120) a weighting (2a) of the learning data records (2); - this weighting (2a) is taken into consideration for training (130) the ANN (1) in monitored fashion on the basis of the samples (11a) and associated labels (12a) contained in the learning data records (2). Trained ANN (1*) and system (50) having this ANN (1*). Associated computer program.
机译:一种用于使用学习数据记录(2)训练人工神经网络(ANN)(1)的方法(100),每个学习数据记录包含一个样本(11a)和一个相关的标签(12a),其中每个样本(11a)代表一个值ANN(1)的一个或多个输入变量(11)和相关标签(12a)代表ANN(1)的一个或多个输出变量(12)的值,其步骤如下:-ANN(1)为根据学习数据记录(2)中包含的样本(11a)以不受监控的方式培训(110); -将学习数据记录(2)中标签(12a)与样本(11a)关联的可靠性和/或质量的至少一个质量标准(3)作为确定(120)权重( 2a)的学习数据记录(2); -在学习数据记录(2)中包含的样本(11a)和相关的标签(12a)的基础上,以加权的方式考虑此权重(2a)以训练(130)ANN(1)。经过训练的ANN(1 *)和具有该ANN(1 *)的系统(50)。关联的计算机程序。

著录项

  • 公开/公告号WO2020193510A1

    专利类型

  • 公开/公告日2020-10-01

    原文格式PDF

  • 申请/专利权人 ROBERT BOSCH GMBH;

    申请/专利号WO2020EP58079

  • 发明设计人 LOU ZHONGYU;NGUYEN DUC TAM;

    申请日2020-03-24

  • 分类号G06N3/08;G06N3/04;

  • 国家 WO

  • 入库时间 2022-08-21 11:09:17

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