Proceedings
Authors
| Filter results2 paper(s) found. |
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1. Machine Learning Pipeline to Estimate Soybean Rust Severity Using UAV-derived Multispectral IndicesAsian Soybean Rust is one of the most destructive diseases affecting soybean crops worldwide and can result in yield losses of up to 90% when control measures are not implemented in a timely manner. Conventional disease monitoring based on field scouting is time-consuming, labor-intensive, and inherently subjective, often failing to adequately represent the spatial variability of disease across production fields. These limitations highlight the need for automated, objective, and high throughput... S.A. Teixeira, R. Valdivino, R. Tsukahara, M. Ribeiro |
2. High Resolution 3D Crop Analysis and Decision Support using UAV LiDAR TechnologyAgriculture is one of the most significant economic activities in Brazil, with coffee cultivation playing a particularly prominent role in the state of Minas Gerais, which leads national production. During the early stages of the coffee growth cycle, systematic monitoring practices are required to assess the spatial uniformity of plant development. These observations support management decisions, including the identification of areas requiring specific interventions and the targeted application... A. Pavanelli, L. Carneiro De Souza, C.E. Inácio, M. De Oliveira, V. Rennó, F. Portelinha, L. Mendes |