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:
Dec. 06, 2022

Filed:

Jul. 04, 2022
Applicants:

Nanjing University of Information Science & Technology, Nanjing, CN;

National Climate Center, Beijing, CN;

Inventors:

Guojie Wang, Nanjing, CN;

Buda Su, Beijing, CN;

Yanjun Wang, Nanjing, CN;

Tong Jiang, Beijing, CN;

Aiqing Feng, Beijing, CN;

Lijuan Miao, Beijing, CN;

Mingyue Lu, Nanjing, CN;

Zhen Dong, Yangzhou, CN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/10 (2022.01); G06V 20/13 (2022.01); G06V 10/62 (2022.01); G06N 3/08 (2006.01); G06V 10/774 (2022.01); G06V 10/77 (2022.01); G06V 10/26 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 20/182 (2022.01); G06N 3/08 (2013.01); G06V 10/26 (2022.01); G06V 10/62 (2022.01); G06V 10/774 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01); G06V 20/13 (2022.01);
Abstract

A method for flood disaster monitoring and disaster analysis based on vision transformer is provided. It includes: step (1), constructing a bi-temporal image change detection model based on vision transformer; step (2), selecting bi-temporal remote sensing images to make flood disaster labels; and step (3), performing flood monitoring and disaster analysis according to the bi-temporal image change detection model constructed in the step (1). In combination with the bi-temporal image change detection model based on an advanced vision transformer in deep learning and radar data which is not affected by time and weather and has strong penetration ability, data when floods occur can be obtained and recognition accuracy is improved.


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