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Streamlined approaches for image classification using principal component analysis and hierarchical clustering of extrudates from coffee and sorghum blends. Author(s): HIDALGO CHÁVEZ, D. W.; SILVA, F. L. C. DA; PINTO, R. V.; CARVALHO, C. W. P. de; FREITAS-SILVA, O. This article describes simple methods to group images including principal component analysis (PCA) and hierarchical clustering of principal components (HCPC). Images of expanded and low expanded extru... ... Repository: BDPA Publication year: 2023
Automatic classification of soybean diseases based on digital images of leaf symptoms. Author(s): BARBEDO, J. G. A.; GODOY, C. V. This paper presents an algorithm for automatic classification of diseases that produce symptons in soybean leaves. Repository: BDPA Publication year: 2015
Developments in forest monitoring under the Brazilian National Forest Inventory: multi-source and hybrid image classification approaches. Author(s): LUZ, N. B. da; OLIVEIRA, Y. M. M. de; ROSOT, M. A. D.; GARRASTAZU, M. C.; MESQUITA JÚNIOR, H. N. de; FREITAS, J. V. de; COSTA, C. R. da Information on forest and tree resources as well as land use and land cover (LULC) maps are a growing demand which Brazilian National Forest Inventory (NFI-BR) is designed to meet through field and re... ... Repository: BDPA Publication year: 2015
The roles of textural images in improving land-cover classification in the Brazilian Amazon. Author(s): LU, D.; LI, G.; MORAN, E.; DUTRA, L.; BATISTELLA, M. Texture has long been recognized as valuable in improving land-cover classification, but how data from different sensors with varying spatial resolutions affect the selection of textural images is poo... ... Repository: BDPA Publication year: 2014
A comparative study of landsat TM and SPOT HRG images of vegetation classification in the brazilian Amazon. Author(s): LU, D.; BATISTELLA, M.; MIRANDA, E. E. de Complex forest structure and abundant tree species in the moist tropical regions often couse difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement i... ... Repository: BDPA Publication year: 2008
Comparison of classification algorithms of images for the mapping of the land covering in Tasso Fragoso municipality, Brazil. Author(s): PEREIRA, P. R. M.; COSTA, F. W. D.; BOLFE, E. L.; MACARRINGE, L.; BOTELHO, A. C. Abstract. One of the main applications of satellite images is the characterization of terrestrial coverage, that from the use of classification techniques, allows the monitoring of spatial transformat... ... Repository: BDPA Publication year: 2021
Individual tree detection and species classification of Amazonian palms using UAV images and deep learning. Author(s): FERREIRA, M. P.; ALMEIDA, D. R. A. de; PAPA, D. de A.; MINERVINO, J. B. S.; VERAS, H. F. P.; FORMIGHIERI, A.; SANTOS, C. A. N.; FERREIRA, M. A. D.; FIGUEIREDO, E. O.; FERREIRA, E. J. L. Information regarding the spatial distribution of palm trees in tropical forests is crucial for commercial exploitation and management. However, spatially continuous knowledge of palms occurrence is s... ... Repository: BDPA Publication year: 2020
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
Self-guided segmentation and classification of multi-temporal landsat 8 images for crop type mapping in southeastern Brazil. Author(s): SCHULTZ, B.; IMMITZER, M.; FORMAGGIO, A. R.; SANCHES, I. D. A.; LUIZ, A. J. B.; ATZBERGER, C. Abstract: Only well-chosen segmentation parameters ensure optimum results of object-based image analysis (OBIA). Manually defining suitable parameter sets can be a time-consuming approach, not necessa... ... Repository: BDPA Publication year: 2015
Land-cover classification in the Brazilian Amazon with satélite images: towards increasing accuracy. Author(s): LU, D.; BATISTELLA, M.; MORAN, E. F. Repository: BDPA Publication year: 2006

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