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:
Aug. 17, 2021

Filed:

Jun. 20, 2019
Applicant:

Waymo Llc, Mountain View, CA (US);

Inventors:

Wan-Yen Lo, Sunnyvale, CA (US);

Abhijit Ogale, Sunnyvale, CA (US);

Yang Gao, Berkeley, CA (US);

Assignee:

Waymo LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06K 9/00 (2006.01); G05D 1/02 (2020.01); G05D 1/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6267 (2013.01); G05D 1/0088 (2013.01); G05D 1/0246 (2013.01); G06K 9/00805 (2013.01); G06K 9/00818 (2013.01); G06K 9/6273 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 3/084 (2013.01);
Abstract

In some implementations, an image classification system of an autonomous or semi-autonomous vehicle is capable of improving multi-object classification by reducing repeated incorrect classification of objects that are considered rarely occurring objects. The system can include a common instance classifier that is trained to identify and recognize general objects (e.g., commonly occurring objects and rarely occurring objects) as belonging to specified object categories, and a rare instance classifier that is trained to compute one or more rarity scores representing likelihoods that an input image is correctly classified by the common instance classifier. The output of the rare instance classifier can be used to adjust the classification output of the common instance classifier such that the likelihood of input images being incorrectly classified is reduced.


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