Estimation of soybean yield parameters under lodging conditions using RGB information from unmanned aerial vehicles

Keyphrases

• UAV 100%
• Yield Parameters 100%
• Lodging 100%
• Soybean Yield 100%
• Regression Logistic 40%
• Deep Learning Neural Network 40%
• Texture Information 40%
• Logistic Regression 20%
• Agriculture 20%
• Politicians 20%
• Food Security 20%
• Image Processing 20%
• China 20%
• Neural Network Model 20%
• Remote Sensing 20%
• Vegetation Index 20%
• Random Forest Regression 20%
• Platform Technology 20%
• Sensor Technology 20%
• Least Squares Support Vector Regression (LSSVR) 20%
• Partial Least Squares Regression 20%
• Canopy Cover 20%
• Unmanned Aerial Vehicle Images 20%
• Growing Season 20%
• Experimental Environment 20%
• Nanchang 20%
• Parameter Dependence 20%
• Glycine Max (L.) Merrill 20%
• Periodic Selection 20%
• Soybean Cultivars 20%
• Flowering Stage 20%
• Regression Support Vector Machine 20%
• Unmanned Aerial Vehicle Platform 20%
• Jiangxi Province 20%
• Early Yield Estimation 20%
• Yield Efficiency 20%
• Multi-source Data Fusion 20%
• Crop Height 20%
• Unmanned Aerial Vehicle Sensors 20%
• Point Data 20%
• Regression Learning 20%

Agricultural and Biological Sciences

• Unmanned Aerial Vehicle 100%
• Neural Network 66%
• Cultivar 66%
• Anthesis 33%
• Vegetation Index 33%
• Least Square 33%
• Support Vector Machine 33%
• Growing Season 33%
• Soybean 33%
• Remote Sensing 33%