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:
Jul. 30, 2024

Filed:

Apr. 04, 2023
Applicant:

Southeast University, Nanjing, CN;

Inventors:

Zhe Li, Nanjing, CN;

Liya Wang, Nanjing, CN;

Xiao Han, Nanjing, CN;

Jie Li, Nanjing, CN;

Qixin Zhang, Nanjing, CN;

Mingjing Dong, Nanjing, CN;

Mingchen Xu, Nanjing, CN;

Shuang Wu, Nanjing, CN;

Yi Shi, Nanjing, CN;

Haini Chen, Nanjing, CN;

Qiaochu Wang, Nanjing, CN;

Assignee:

SOUTHEAST UNIVERSITY, Nanjing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/00 (2022.01); A61B 5/0205 (2006.01); A61B 5/0533 (2021.01); A61B 5/352 (2021.01); A61B 5/378 (2021.01); A61B 5/397 (2021.01); G06N 20/00 (2019.01); G06V 10/26 (2022.01); G06V 10/764 (2022.01); G06V 20/00 (2022.01); G06Q 50/26 (2012.01);
U.S. Cl.
CPC ...
A61B 5/378 (2021.01); A61B 5/0205 (2013.01); A61B 5/0533 (2013.01); A61B 5/352 (2021.01); A61B 5/397 (2021.01); G06N 20/00 (2019.01); G06V 10/26 (2022.01); G06V 10/764 (2022.01); G06V 20/39 (2022.01); A61B 2503/12 (2013.01); G06Q 50/26 (2013.01);
Abstract

A street greening quality detection method based on physiological activation recognition is provided. The street greening quality detection method includes establishing a greening quality factor index system, and obtaining and uniformly processing street greening images; collecting raw data, and performing reclassification and differential wave processing on the raw data to obtain valid physiological data that can be used for activation feature recognition of greening quality factors; calculating physiological activation feature parameters, training the physiological activation feature parameters by transfer learning fusion to determine importance of physiological activation features, and recognizing weighted average greening activation indexes of the greening quality factors; analyzing weighted average greening activation index data of the greening quality factors to form a street greening quality detection model; and inputting annotated street samples to be analyzed into the street greening quality detection model to obtain annotated results of street greening quality grading detection target data.


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