The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 11, 2025

Filed:

Jul. 21, 2022
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventor:

Frank Schmidt, Leonberg, DE;

Assignee:

ROBERT BOSCH GMBH, Stuttgart, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); B60W 40/02 (2006.01); G06N 3/082 (2023.01); G06V 10/44 (2022.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); H04N 19/85 (2014.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06V 10/761 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); B60W 40/02 (2013.01); G06N 3/082 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01); H04N 19/85 (2014.11);
Abstract

A device, a method and a computer program for training and/or verifying the robustness of an artificial neural network. The artificial neural network is designed to determine an output variable. The method includes: predefining an input variable for the network which has a plurality of dimensions. For each dimension of the input variable or for each dimension of an output of a linear layer of the artificial neural network without an activation function to which the input variable is mapped by the artificial neural network, the method includes a determination of an upper input variable limit for which a disturbance variable model by which the input variable is able to be mapped to a disturbed input variable has the highest possible value in the dimension, and a determination of a lower input variable limit for which the disturbance variable model has the lowest value possible in the dimension.


Find Patent Forward Citations

Loading…