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:
Jul. 14, 2026

Filed:

Mar. 09, 2023
Applicants:

Bull Sas, Les Clayes-sous-Bois, FR;

Universite Grenoble Alpes, Saint Martin d'Heres, FR;

Institut Polytechnique DE Grenoble, Grenoble, FR;

Centre National DE LA Recherche Scientifique, Paris, FR;

Inventors:

Loïc Pauletto, Grenoble, FR;

Massih-Reza Amini, La Terrasse, FR;

Assignees:

BULL SAS, Les Clayes-sous-Bois, FR;

UNIVERSITE GRENOBLE ALPES, Saint Martin d'Heres, FR;

INSTITUT POLYTECHNIQUE DE GRENOBLE, Grenoble, FR;

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFQUE, Paris, FR;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/0464 (2023.01); G06N 3/0895 (2023.01); G06N 3/09 (2023.01);
U.S. Cl.
CPC ...
G06N 3/0464 (2023.01); G06N 3/0895 (2023.01); G06N 3/09 (2023.01);
Abstract

The invention relates to a method for training a dynamic-architecture convolutional neural network for semantic image segmentation, including auto-annotation of images, to constitute a first image database of auto-annotated images. The method includes applying at least one transformation to at least one source image, and adding, to each transformed image thus obtained, a first tag corresponding to the transformation. The method also includes at least one iteration of a phase including training the neural network with the first image database, and a second image database annotated with a second tag relating to the content of the image. The invention also relates to a computer program and a device implementing the method, and a deep-learning dynamic-architecture convolutional neural network obtained by the method.


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