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InsectCV: a system for insect detection in the lab from trap images. Author(s): CESARO JÚNIOR, T. de; RIEDER, R.; DI DOMÊNICO, J. R.; LAU, D. Advances in artificial intelligence, computer vision, and high-performance computing have enabled the creation of efficient solutions to monitor pests and identify plant diseases. In this context, we... ... Repository: BDPA Publication year: 2021
YOLO performance analysis for real-time detection of soybean pests. Author(s): TETILA, E. C.; SILVEIRA, F. A. G. da; COSTA, A. B. da; AMORIM, W. P.; ASTOLFI, G.; PISTORI, H.; BARBEDO, J. G. A. In this work, we evaluated the You Only Look Once (YOLO) architecture for real-time detection of soybean pests. Repository: BDPA Publication year: 2024
Mapeamento de falhas de plantio em lavoura de cana-de-açúcar em espaços ocupados por plantas daninhas a partir de imagens de VANTs utilizando ImageJ. Author(s): YANO, I. H.; SPERANZA, E. A.; CRUZ, S. A. B. da; SALVAIA, F. P. Identificar e mapear falhas de plantio em lavouras de cana-de-açúcar em espaços ocupados por plantas daninhas a partir de imagens de VANTs Existem diversos trabalhos realizados para identificar falhas... ... Repository: BDPA Publication year: 2021
Testando a rede neural YOLOv5 para detecção de frutos em pomares de laranja. Author(s): RIBEIRO, A. F.; SOUZA, K. X. S. de; CAMARGO NETO, J.; TERNES, S.; YANO, I. H. Este trabalho, tem como objetivo analisar a viabilidade do emprego de algoritmos computacionais por meio de redes neurais e visão computacional no processo de contagem de frutos através de imagens dig... ... Repository: BDPA Publication year: 2022
Simultaneous detection of Nosema spp., Ascosphaera apis and Paenibacillus larvae in honey bee products. Author(s): GUIMARÃES-CESTARO, L.; SERRÃO, J. E.; MESSAGE, D.; MARTINS, M. F.; TEIXEIRA, É. W. Abstract Honey bees are responsible for pollinating many native and cultivated plant species. These insects can be affected by many pathogens, including fungi and bacteria, both of which can form spor... ... Repository: BDPA Publication year: 2016
Selection indices for Nellore production systems in the Brazilian Cerrado. Author(s): PORTES, J. V.; MENEZES, G. R. O.; MacNEIL, M. D.; SILVA, L. O. C. da; GONDO, A.; BRACCINI NETO, J. Repository: BDPA Publication year: 2020
A segmentation approach to delineate zones for differential nitrogen intervention. Author(s): OLIVEIRA, R. P. de; WHELAN, B.; MCBRATNEY, A. Multi-source and -temporal data integration is expected to support the delineation of within-field management zones that may better conform to unique combinations of crop yield variations. This work a... ... Repository: BDPA Publication year: 2013
Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid - data, methods and first results. Author(s): BEUCHLE, R.; EVA, H. D.; MIRANDA, E. E. de; HOLLER, W. A.; OSHIRO, O. T.; ACHARD, F. At the Joint Research Centre (JRC) of the European Commission, a methodology has been developed to monitor the pan-tropical forest cover with remote sensing data for the years 1990-2000-2005 in Latin... ... Repository: BDPA Publication year: 2011
Prediction of cattle density and location at the frontier of Brazil and Paraguay using remote sensing. Author(s): AMARAL, T. B.; GOND, V.; TRAN, A. Repository: BDPA Publication year: 2014
A mathematical model to estimate the volume of grey water of pesticide mixtures. Author(s): PARAIBA, L. C.; PAZIANOTTO, R. A. A.; LUIZ, A. J. B.; MAIA, A. de H. N.; JONSSON, C. M. The usual method to calculate grey water footprint does not take into account the volume of water required to dilute concentrations of pesticide mixtures in freshwater and it also depends on maximum c... ... Repository: BDPA Publication year: 2014

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