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:
Nov. 05, 2024

Filed:

Oct. 29, 2021
Applicant:

Zoox, Inc., Foster City, CA (US);

Inventors:

Clement Besson, San Francisco, CA (US);

Scott M. Purdy, Lake Forest Park, WA (US);

Bharadwaj Raghavan, Sunnyvale, CA (US);

Assignee:

Zoox, Inc., Foster City, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/56 (2022.01); B60W 60/00 (2020.01); G06N 3/08 (2023.01); G06T 7/73 (2017.01); G06V 10/25 (2022.01);
U.S. Cl.
CPC ...
G06V 20/56 (2022.01); B60W 60/00 (2020.02); G06N 3/08 (2013.01); G06T 7/73 (2017.01); G06V 10/25 (2022.01); B60W 2556/45 (2020.02); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2210/12 (2013.01);
Abstract

Techniques for evaluating and validating progress of training machine-learned models are described herein. The techniques may include storing, in a database, metric data associated with outputs from machine-learned models based on sensor data inputs. For instance, the metric data may include first metric data associated with a first bounding box output by a machine-learned model and second metric data associated with a second bounding box output by an updated version of the machine-learned model. The techniques also include a graphical user interface (GUI) for presenting visualizations of the metric data that improve the ability to evaluate the performance of a machine-learned model. In some examples, an indication of a request to evaluate the updated version of the machine-learned model may be received via the GUI. Based on the indication, the GUI may cause presentation of visualization(s) of difference(s) between first metric(s) of the first metric data and second metric(s) of the second metric data.


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