Monitoring of agricultural progress in rice-wheat rotation area based on UAV RGB images.

ABSTRACT: Real-time monitoring of rice-wheat rotation areas is crucial for improving agricultural productivity and ensuring the overall yield of rice and wheat. However, the current monitoring methods mainly rely on manual recording and observation, leading to low monitoring efficiency. This study addresses the challenges of monitoring agricultural progress and the time-consuming and labor-intensive nature of the monitoring process. By integrating Unmanned aerial vehicle (UAV) image analysis technology and deep learning techniques, we proposed a method for precise monitoring of agricultural progress in rice-wheat rotation areas. The proposed method was initially used to extract color, texture, and convolutional features from RGB images for model construction. Then, redundant features were removed th

SUBMITTER: Wang J 

PROVIDER: S-EPMC11754401 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature