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:
Jan. 07, 2025

Filed:

Sep. 22, 2023
Applicant:

Deere & Company, Moline, IL (US);

Inventors:

Jie Yang, Sunnyvale, CA (US);

Zhiqiang Yuan, San Jose, CA (US);

Hongxu Ma, San Jose, CA (US);

Cheng-en Guo, Santa Clara, CA (US);

Elliott Grant, Woodside, CA (US);

Yueqi Li, San Jose, CA (US);

Assignee:

DEERE &COMPANY, Moline, IL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/74 (2022.01); G05D 1/00 (2006.01); G06F 18/20 (2023.01); G06F 18/214 (2023.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G06V 10/20 (2022.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01); G06V 20/20 (2022.01);
U.S. Cl.
CPC ...
G06T 7/001 (2013.01); G05D 1/0033 (2013.01); G06F 18/214 (2023.01); G06F 18/285 (2023.01); G06N 3/0418 (2013.01); G06N 3/08 (2013.01); G06V 10/255 (2022.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 20/188 (2022.01); G06V 20/20 (2022.01);
Abstract

Implementations are described herein for training and applying machine learning models to digital images capturing plants, and to other data indicative of attributes of individual plants captured in the digital images, to recognize individual plants in distinction from other individual plants. In various implementations, a digital image that captures a first plant of a plurality of plants may be applied, along with additional data indicative of an additional attribute of the first plant observed when the digital image was taken, as input across a machine learning model to generate output. Based on the output, an association may be stored in memory, e.g., of a database, between the digital image that captures the first plant and one or more previously-captured digital images of the first plant.


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