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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
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Detección precisa de enfermedades en hojas de té mediante teledetección de baja altitud con UAV y modelo YOLO11

Yaojun Zhang1, Guiling Wu1, Jianbo Shen2,3

  • 1School of Information Engineering, Xinyang Agriculture and Forestry University, Xinyang, Henan, China.

PloS one
|February 18, 2026
PubMed
Resumen

Este estudio presenta FCHE-YOLO, un modelo ligero mejorado para detectar enfermedades en hojas de té utilizando drones. Logra mayor precisión y velocidad, lo que lo hace ideal para el despliegue en el borde en vehículos aéreos no tripulados (UAV).

Palabras clave:
FCHE-YOLOdetección de enfermedades en hojas de tévehículo aéreo no tripulado (UAV)teledetección de baja altitudmodelo YOLO11 optimizadovisión por computadoraaprendizaje profundoagricultura de precisión

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