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:
Jan. 30, 2024

Filed:

Jun. 28, 2021
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Artem Moskalev, Amsterdam, NL;

Ivan Sosnovik, Amsterdam, NL;

Arnold Smeulders, Amsterdam, NL;

Konrad Groh, Stuttgart, DE;

Assignee:

ROBERT BOSCH GMBH, Stuttgart, DE;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06T 7/246 (2017.01); G05D 1/02 (2020.01); G06V 20/56 (2022.01); G06F 18/21 (2023.01); G06F 18/213 (2023.01); G06V 10/75 (2022.01); G06V 10/80 (2022.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G05D 1/0214 (2013.01); G06F 18/213 (2023.01); G06F 18/217 (2023.01); G06T 7/248 (2017.01); G06V 10/454 (2022.01); G06V 10/757 (2022.01); G06V 10/806 (2022.01); G06V 20/56 (2022.01); G05D 2201/0213 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30252 (2013.01);
Abstract

A method for recognizing at least one object in at least one input image. In the method, a template image of the object is processed by a first convolutional neural network (CNN) to form at least one template feature map; the input image is processed by a second CNN to form at least one input feature map; the at least one template feature map is compared to the at least one input feature map; it is evaluated from the result of the comparison whether and possibly at which position the object is contained in the input image, the convolutional neural networks each containing multiple convolutional layers, and at least one of the convolutional layers being at least partially formed from at least two filters, which are convertible into one another by a scaling operation.


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