- 专利标题: Method and device for training a machine learning system
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申请号: US17610669申请日: 2020-06-10
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公开(公告)号: US12100197B2公开(公告)日: 2024-09-24
- 发明人: Lydia Gauerhof , Nianlong Gu
- 申请人: Robert Bosch GmbH
- 申请人地址: DE Stuttgart
- 专利权人: ROBERT BOSCH GMBH
- 当前专利权人: ROBERT BOSCH GMBH
- 当前专利权人地址: DE Stuttgart
- 代理机构: NORTON ROSE FULBRIGHT US LLP
- 代理商 Gerard A. Messina
- 优先权: DE 2019209566.6 2019.06.28
- 国际申请: PCT/EP2020/066033 2020.06.10
- 国际公布: WO2020/260016A 2020.12.30
- 进入国家日期: 2021-11-11
- 主分类号: G06V10/82
- IPC分类号: G06V10/82 ; G06N3/045 ; G06N3/088 ; G06V10/764
摘要:
A method for training a machine learning system. The method includes generating an augmented dataset including input images for training the machine learning system, which is for classification and/or semantic segmentation of input images, using a first machine learning system, which is embodied as a decoder of an autoencoder, and a second machine learning system, which is embodied as an encoder of the autoencoder. Latent variables are ascertained from the input images using the encoder. The input images are classified as a function of ascertained feature characteristics of their image data. An augmented input image of the augmented dataset is ascertained from at least one of the input images as a function of average values of the ascertained latent variables in at least two of the classes. The image classes are selected so that the input images classified therein agree in their characteristics in a predefinable set of other features.
公开/授权文献
- US20220245932A1 METHOD AND DEVICE FOR TRAINING A MACHINE LEARNING SYSTEM 公开/授权日:2022-08-04
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