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. 15, 2025

Filed:

Apr. 26, 2021
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Dan Zhang, Leonberg, DE;

Kanil Patel, Stuttgart, DE;

William Harris Beluch, Stuttgart, DE;

Assignee:

ROBERT BOSCH GMBH, Stuttgart, DE;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06F 17/16 (2006.01); G06F 17/18 (2006.01); G06N 3/047 (2023.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06N 3/047 (2023.01);
Abstract

A computer-implemented method of calibrating a trained classification model. The trained classification model is trained to classify input samples according to a plurality of classes and to provide associated prediction probabilities, and includes a plurality of hidden layers and at least one activation layer. The method includes accessing the trained classification model and accessing a plurality of validation samples, each validation sample having a ground-truth label, the ground-truth label indicating a ground-truth class. The method further includes applying the trained classification model to the plurality of validation samples, obtaining, for each validation sample, an output logit vector from a layer of the trained classification model preceding a last activation layer, and training a calibration module. The calibration module is trained to adjust prediction probabilities, the prediction probabilities being derived from the output logit vectors.


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