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. 04, 2025

Filed:

Feb. 08, 2021
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Christian Heinzemann, Ludwigsburg, DE;

Christoph Gladisch, Renningen, DE;

Jens Oehlerking, Stuttgart, DE;

Konrad Groh, Stuttgart, DE;

Matthias Woehrle, Bietigheim-Bissingen, DE;

Michael Rittel, Markgroeningen, DE;

Oliver Willers, Korb, DE;

Sebastian Sudholt, Besigheim, DE;

Assignee:

ROBERT BOSCH GMBH, Stuttgart, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/58 (2022.01); G06T 1/00 (2006.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 20/64 (2022.01);
U.S. Cl.
CPC ...
G06V 20/58 (2022.01); G06T 1/0014 (2013.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/7747 (2022.01); G06V 10/776 (2022.01); G06V 20/64 (2022.01); G06V 2201/06 (2022.01);
Abstract

A computer-implemented method for evaluating an image classifier, in which a classifier output of the image classifier is provided for the actuation of an at least semi-autonomous robot. The evaluation method includes: ascertaining a first dataset including image data and annotations being assigned to the image data, the annotations including information about the scene imaged in the respective image and/or about image regions to be classified and/or about movement information of the robot; ascertaining regions of the scenes that are reachable by the robot based on the annotations; ascertaining relevance values for image regions to be classified by the image classifier; classifying the image data of the first image dataset with the aid of the image classifier; evaluating the image classifier based on image regions correctly classified by the image classifier and incorrectly classified image regions, as well as the calculated relevance values of the corresponding image regions.


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