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.
Patent No.:
Date of Patent:
Nov. 19, 2024
Filed:
Oct. 02, 2023
Zhejiang Lab, Hangzhou, CN;
Fen Xu, Hangzhou, CN;
Yinxing Ma, Hangzhou, CN;
Xiaogang Xu, Hangzhou, CN;
Xinghua Wei, Hangzhou, CN;
Jun Wang, Hangzhou, CN;
Yaolong Yang, Hangzhou, CN;
Mengchen Zhang, Hangzhou, CN;
Yue Feng, Hangzhou, CN;
ZHEJIANG LAB, Hangzhou, CN;
Abstract
Provided in the present invention is a method for intelligent identification of rice growth potential based on unmanned aerial vehicle (UAV) monitoring, the method including the following steps: obtaining rice plot images, labeling the images, establishing a deep convolutional neural network detection model, using the labeled rice plot images to optimize and train the model, inputting the rice plot images to be measured into the trained model, and detecting a location of a rice plot target frame in each image; selecting a target frame with the largest area in each rice plot image, and pre-processing a rice plot image in the target frame; and calculating a vegetation coverage rate of the pre-processed rice plot image, and determining a level of rice growth potential according to the vegetation coverage rate. Also provided in the present invention is a system for intelligent identification of rice growth potential based on unmanned aerial vehicle (UAV) monitoring. The method of the present invention has the advantages of simplicity, high precision, fast speed and low cost in the identification of the rice growth potential, and can be widely used in automatic and intelligent production management of agriculture.