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:
Apr. 14, 2026

Filed:

Oct. 04, 2021
Applicant:

At&t Intellectual Property I, L.p., Atlanta, GA (US);

Inventors:

Eric Zavesky, Austin, TX (US);

Raghuraman Gopalan, Dublin, CA (US);

Behzad Shahraray, Holmdel, NJ (US);

David Crawford Gibbon, Lincroft, NJ (US);

Bernard S. Renger, New Providence, NJ (US);

Paul Triantafyllou, Watchung, NJ (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); B60W 30/095 (2012.01); G05D 1/00 (2006.01); G06F 18/2413 (2023.01); G06N 5/022 (2023.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/64 (2022.01); B60W 30/09 (2012.01); B64U 101/30 (2023.01); G06V 20/13 (2022.01);
U.S. Cl.
CPC ...
G06V 10/82 (2022.01); B60W 30/0953 (2013.01); G05D 1/0088 (2013.01); G05D 1/0094 (2013.01); G06F 18/2413 (2023.01); G06N 5/022 (2013.01); G06V 10/764 (2022.01); G06V 20/56 (2022.01); G06V 20/64 (2022.01); B60W 30/09 (2013.01); B64U 2101/30 (2023.01); B64U 2201/10 (2023.01); G05D 1/0246 (2013.01); G06V 20/13 (2022.01);
Abstract

Methods, computer-readable media, and devices are disclosed for improving an object model based upon measurements of physical properties of an object via an unmanned vehicle using adversarial examples. For example, a method may include a processing system capturing measurements of physical properties of an object via at least one unmanned vehicle, updating an object model for the object to include the measurements of the physical properties of the object, where the object model is associated with a feature space, and generating an example from the feature space, where the example comprises an adversarial example. The processing system may further apply the object model to the example to generate a prediction, capture additional measurements of the physical properties of the object via the at least one unmanned vehicle when the prediction fails to identify that the example is an adversarial example, and update the object model to include the additional measurements.


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