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Author

G. Lyra

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Open access 2026

Comparison of machine learning techniques for identifying weeds in maize crops

ABSTRACT The present study was conducted at the Federal Rural University of Rio de Janeiro, in the years 2024 and 2025, to evaluate the performance of three supervised classifiers - maximum likelihood, random forest, and support vector machine - for spectral discrimination between maize (Zea mays L.) and the weed (Cype...

T. M. de Souza, M. M. de Barros, J. C. de Siqueira et al. · 0 citations
Open access 2026

Fried Parameter-Based Cost Function for Dynamic Metropolitan Free-Space Optics Circuit Routing

This paper introduces an AT-aware dynamic circuit routing framework that leverages real-time environmental measurements from public meteorological stations, enabling greedy-based routing algorithms to compute optimal paths within a representative topology in Rio de Janeiro, Brazil.

Felipe B. Bittar, G. Lyra, Roberto B. Di Renna et al. · 0 citations

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