Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach. [PDF]
Basil N +11 more
europepmc +1 more source
Abstract Traditionally, turfgrass color has been assessed through visual ratings or light box‐based digital image analysis, methods that are either subjective or labor‐intensive. In this study, we evaluated the potential of unmanned aerial vehicle (UAV)‐based multispectral and red‐green‐blue (RGB) imagery as a high‐throughput alternative for capturing ...
Ved Parkash +9 more
wiley +1 more source
First Analysis and Experiments in Aerial Manipulation Using fully Actuated Redundant Robot Arm.
Dominik Sommer +19 more
core +1 more source
Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles. [PDF]
Alrayes FS +7 more
europepmc +1 more source
Abstract Monitoring spatial variations in plant growth and forecasting yield before harvest provides valuable insights for optimizing agronomic decision‐making in potato (Solanum tuberosum L.) cultivation. Although unmanned aerial vehicle (UAV)‐based remote sensing has recently enabled the development of tuber fresh weight (TW) estimation models, their
Yuto Imachi +7 more
wiley +1 more source
NavBLIP: a visual-language model for enhancing unmanned aerial vehicles navigation and object detection. [PDF]
Li Y +6 more
europepmc +1 more source
Drone‐based phenotyping of maize for multiple disease resistance and yield in breeding field trials
Abstract Improving selection for multiple disease resistance (MDR) and yield in maize (Zea mays L.) requires high‐throughput, objective phenotyping tools, particularly under field conditions where several foliar diseases co‐occur. We evaluated drone‐based multispectral vegetation indices (VIs) for predicting resistance to northern leaf blight (NLB ...
Danilo E. Moreta +7 more
wiley +1 more source
Research on Mobile Network Parameters Using Unmanned Aerial Vehicles. [PDF]
Warczek J +4 more
europepmc +1 more source
Abstract Data from high‐throughput phenotyping (HTP) could be used for phenotype imputation to enhance genomic selection (GS) or gene discovery, but this has not been explored in crop species. Three machine learning models: multiple linear regression (MLR), missForest, and k‐nearest neighbors, were evaluated for grain yield (GY) phenotype imputation in
Raysa Gevartosky +2 more
wiley +1 more source
Unmanned aerial vehicles for human detection and recognition using neural-network model. [PDF]
Abbas Y +6 more
europepmc +1 more source

