首页|University of Novi Sad Researcher Furthers Understanding of Machine Learning (Vineyard Zoning and Vine Detection Using Machine Learning in Unmanned Aerial Vehicle Imagery)
University of Novi Sad Researcher Furthers Understanding of Machine Learning (Vineyard Zoning and Vine Detection Using Machine Learning in Unmanned Aerial Vehicle Imagery)
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Investigators publish new report on artificial intelligence. According to news reporting originating from Novi Sad, Serbia, by NewsRx correspondents, research stated, "Precision viticulture systems are essential for enhancing traditional intensive viticulture, achieving high-quality results, and minimizing costs." The news journalists obtained a quote from the research from University of Novi Sad: "This study explores the integration of Unmanned Aerial Vehicles (UAVs) and artificial intelligence in precision viticulture, focusing on vine detection and vineyard zoning. Vine detection employs the YOLO (You Only Look Once) deep learning algorithm, achieving a remarkable 90% accuracy by analysing UAV imagery with various spectral ranges from various phenological stages. Vineyard zoning, achieved through the application of the K-means algorithm, incorporates geospatial data such as the Normalized Difference Vegetation Index (NDVI) and the assessment of nitrogen, phosphorus, and potassium content in leaf blades and petioles. This approach enables efficient resource management tailored to each zone's specific needs. The research aims to develop a decision-support model for precision viticulture. The proposed model demonstrates a high vine detection accuracy and defines management zones with variable weighting factors assigned to each variable while preserving location information, revealing significant differences in variables."
University of Novi SadNovi SadSerbiaEuropeCyborgsEmerging TechnologiesMachine Learning
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