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:
Sep. 19, 2023

Filed:

Jul. 29, 2022
Applicant:

Guangdong Polytechnic Normal University, Guangzhou, CN;

Inventors:

Zhiping Tan, Guangzhou, CN;

Yu Tang, Guangzhou, CN;

Jiepeng Yang, Guangzhou, CN;

Yiqing Fu, Guangzhou, CN;

Jinfei Zhao, Guangzhou, CN;

Jiahao Li, Guangzhou, CN;

Qiwei Guo, Guangzhou, CN;

Huasheng Huang, Guangzhou, CN;

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A01G 22/05 (2018.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01); G06V 10/774 (2022.01); A01B 79/00 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A01B 79/005 (2013.01); A01G 22/05 (2018.02); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/188 (2022.01); G06T 2207/10028 (2013.01); G06T 2207/10036 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30188 (2013.01);
Abstract

The present invention relates to the technical field of field crop cultivation, more particularly to a training method, an evaluation method, an electronic device and a storage medium. According to the present invention, a multispectral three-dimensional point cloud map is obtained through depth information and multispectral information, and the multispectral three-dimensional point cloud map is analyzed by utilizing an FVNet three-dimensional target detection algorithm, thereby acquiring crop feature information. Thus, more comprehensive crop information can be obtained, and a crop state evaluation model constructed based on an artificial neural network can be further trained with the crop feature information.


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