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:
May. 14, 2024

Filed:

Jun. 24, 2020
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Nilesh Ahuja, Cupertino, CA (US);

Ignacio J. Alvarez, Portland, OR (US);

Ranganath Krishnan, Hillsboro, OR (US);

Ibrahima J. Ndiour, Portland, OR (US);

Mahesh Subedar, Laveen, AZ (US);

Omesh Tickoo, Portland, OR (US);

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G05B 13/02 (2006.01); G06F 18/2431 (2023.01); G06F 18/25 (2023.01); G06N 5/046 (2023.01); G06N 7/01 (2023.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G05B 13/026 (2013.01); G05B 13/027 (2013.01); G06F 18/2431 (2023.01); G06F 18/251 (2023.01); G06N 5/046 (2013.01); G06N 7/01 (2023.01);
Abstract

Techniques are disclosed for using neural network architectures to estimate predictive uncertainty measures, which quantify how much trust should be placed in the deep neural network (DNN) results. The techniques include measuring reliable uncertainty scores for a neural network, which are widely used in perception and decision-making tasks in automated driving. The uncertainty measurements are made with respect to both model uncertainty and data uncertainty, and may implement Bayesian neural networks or other types of neural networks.


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