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Data fusion in agriculture: resolving ambiguities and closing data gaps. Author(s): BARBEDO, J. G. A. Abstract. Acquiring useful data from agricultural areas has always been somewhat of a challenge, as these are often expansive, remote, and vulnerable to weather events. Despite these challenges, as te... ... Repository: BDPA Publication year: 2022
Multilevel data fusion for the internet of things in smart agriculture. Author(s): TORRES, A. B. B.; ROCHA, A. R. DA; SILVA, T. L. C. DA; SOUZA, J. N. DE; GONDIM, R. S. Repository: BDPA Publication year: 2020
Remote and proximal sensors data fusion: digital twins in irrigation management zoning. Author(s): RODRIGUES, H.; CEDDIA, M. B.; TASSINARI, W.; VASQUES, G. M.; BRANDAO, Z. N.; MORAIS, J. P. S.; OLIVEIRA, R. P. de; NEVES, M. L.; TAVARES, S. R. de L. The scientific field of precision agriculture employs increasingly innovative techniques to optimize inputs, maximize profitability, and reduce environmental impact. However, obtaining a high number o... ... Repository: BDPA Publication year: 2024
Proximal and remote sensor data fusion for in-depth salinization mapping in the Brazilian semiarid via machine learning. Author(s): TAVARES, S. R. de L.; VASQUES, G. de M.; OLIVEIRA, R. P. de; DANTAS, M. M.; RODRIGUES, H. M. Mapping the salinization in irrigated cropland is a challenging practice. As an alternative, data from proximal and remote sensors have been implemented together via datafusion and machine learning al... ... Repository: BDPA Publication year: 2022
Land use/cover classification in the Brazilian Amazon using satellite images. Author(s): LU, D.; BATISTELLA, M.; LI, G.; MORAN, E.; HETRICK, S.; FREITAS, C. DA C.; SANT'ANNA, S. J. Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical... ... Repository: BDPA Publication year: 2012
Geographical traceability of South Brazilian red wines through fused spectroscopic data. Author(s): SCHNEIDER, M. P.; BOCK, F. C.; GUERRA, C. C.; SILVA, L. L.; FERRÃO, M. F.; GOMES, A. A. The state of Rio Grande do Sul is the largest national wine producer, being the regions of Serra Gaúcha and Campanha the most out standing. Repository: BDPA Publication year: 2019
Mapping integrated crop–livestock systems using fused Sentinel-2 and PlanetScope time series and deep learning. Author(s): WERNER, J. P. S.; BELGIU, M.; BUENO, I. T.; REIS, A. A. dos; TORO, A. P. S. G. D.; ANTUNES, J. F. G.; STEIN, A.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G.; COUTINHO, A. C.; ESQUERDO, J. C. D. M.; FIGUEIREDO, G. K. D. A. The main objective of this research was to develop a method for mapping ICLS using deep learning algorithms applied on Satellite Image Time Series (SITS) data cubes, which consist of Sentinel-2 (S2) a... ... Repository: BDPA Publication year: 2024
Mapeamento de pastagens por meio da classificação da fusão de imagens Landsat-8/OLI e MODIS no município de São Gabriel do Oeste - MS. Author(s): CAON, I. L.; MERCANTE, E.; ANTUNES, J. F. G.; CATTANI, C. E. V.; MENDES, I. S.; OLDONI, L. V. Resumo. O sensoriamento remoto mostra-se eficiente no mapeamento de grandes áreas geográficas, executado a partir de imagens orbitais. A alta resolução espacial presente em sensores tem permitido o ma... ... Repository: BDPA Publication year: 2018
The nucleoprotein of Tomato spotted wilt virus as protein tag for easy purification and enhanced production of recombinant proteins in plants. Author(s): LACORTE, C.; RIBEIRO, S. G.; LOHUIS, D.; GOLDBACH, R.; PRINS, M. Repository: BDPA Publication year: 2007
A comparison of multisensor integration methods for land cover classification in the Brazilian Amazon. Author(s): LU, D.; LI, G.; MORAN, E.; DUTRA, L.; BATISTELLA, M. Many data fusion methods are available, but it is poorly understood which fusion method is suitable for integrating Landsat Thematic Mapper (TM) and radar data for land cover classification. This rese... ... Repository: BDPA Publication year: 2011

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