To improve crop nutrient estimation, we proposed a novel hybrid method that integrates the computational efficiency of AI models with the robustness of physics-based Radiative...
Our proposed unsupervised pre-training strategy mitigated the requirement of intensive training data for deep learning models. Leveraging unlabeled UAV-collected RGB images, this approach significantly enhanced...
We employed UAV-based multimodal images, including RGB, multispectral, and thermal data, to evaluate the drought tolerance of bioenergy sorghum. By leveraging the concept of drought...
Plant phenotypes are the observable traits of a plant, like height and leaf size. High-throughput plant phenotyping (HTPP) is a burgeoning technology facilitating rapid and...
Data pipelines were created to extract multiple crop structural features, such as plant height and leaf area index, from three-dimensional (3D) LiDAR (Light Detection and...