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| Filter results2 paper(s) found. |
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1. Application for Pixel-level Segmentation and Quantification of Lignified Fibers (Sclerenchyma) and Parenchyma in Microscopic Images of Sugarcane CulmsQuantifying lignified tissues in sugarcane culms (Saccharum spp.) is essential for anatomical characterizations and for inferences related to biomass quality and the potential uses of plant material. Conventional methods may require specific laboratory procedures and manual steps in digital analysis, increasing processing time and reliance on skilled operators. In this context, computer vision techniques applied to microscopic images constitute an accessible and reproducible alternative,... G.F. Rubio, J.F. Rubio, L.E. Pereira, J.R. Marques, A.R. Tech, M.F. Logli |
2. Detection of latrine areas in equine paddocks using drones and computer visionEquines can exhibit behaviors that are harmful to the soil, such as spatial segregation, which is caused by their selective grazing pattern. This species may choose its feeding areas based on vegetation structural characteristics, such as forage density, leaf availability, and stage of maturity (which are perceived through their tactile receptors). When present daily, this natural behavior can impair soil health, as spatial segregation within paddocks intensifies and latrine (dung) areas form.... |