Detection of tangled lignum (Duma florulenta) from UAVs using imagery and machine learning

Keyphrases

• Machine Learning 100%
• Lignum 100%
• UAV 100%
• Duma Florulenta 100%
• LiDAR 17%
• Percent Cover 17%
• Digital Surface Model 17%
• Flooding Events 11%
• Environmental Water 11%
• Condition Index 11%
• Machine Learning Models 11%
• Environmental Watering 11%
• Height Classes 11%
• Field-based Approach 11%
• Quality Classes 11%
• Model Output 5%
• Condition Classes 5%
• Class Size 5%
• Wetlands 5%
• Hattah Lakes 5%
• Model Accuracy 5%
• High-resolution Imagery 5%
• Model Improvement 5%
• Opportunity to Use 5%
• Convolutional Neural Network 5%
• Overall Accuracy 5%
• Convolutional Neural Network Model 5%
• Field-based Data 5%
• Feature Class 5%
• Watering Regime 5%
• RGB Imagery 5%
• Wetland Attributes 5%
• Unpiloted Aerial Vehicles 5%

Agricultural and Biological Sciences

• Unmanned Aerial Vehicle 100%
• Learning System 100%
• Machine Learning 100%
• Neural Network 33%

Earth and Planetary Sciences

• Machine Learning 100%
• Unmanned Aerial Vehicle 100%
• Optical Radar 50%