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:
Mar. 18, 2025

Filed:

Jan. 10, 2020
Applicants:

Robert Bosch Gmbh, Stuttgart, DE;

Carnegie Mellon University, Pittsburgh, PA (US);

Inventors:

Jeremiah M. Cohen, Pittsburgh, PA (US);

Frank Schmidt, Leonberg, DE;

Jeremy Zieg Kolter, Pittsburgh, PA (US);

Assignees:

ROBERT BOSCH GMBH, Stuttgart, DE;

CARNEGIE MELLON UNIVERSITY, Pittsburgh, PA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 18/2415 (2023.01); G06F 18/21 (2023.01); G06F 18/2431 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/2193 (2023.01); G06F 18/2415 (2023.01); G06F 18/2431 (2023.01); G06N 7/01 (2023.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01);
Abstract

A computer-implemented method for assessing a robustness of a smoothed classifier for classifying sensor signals received from a sensor. The method includes: providing an input signal depending on the sensor signal, determining, by the smoothed classifier, a first value which characterizes a probability that the input signal, when subjected to noise will be classified as belonging to a first class, wherein the first class is a most probable class, determining, by the smoothed classifier, a second value which characterizes a probability that the input signal, when subjected to the noise, will be classified as belonging to a second class, wherein the second class is a second-most probable class, determining a robustness value on a first inverse value of a standard Gaussian cumulative distribution function at the first value and/or depending on a second inverse value of the standard Gaussian cumulative distribution function at the second value.


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