Resultados de búsqueda - "computing"

  1. In-Line Estimation of the Standard Colour Index of Citrus Fruits Using a Computer Vision System Developed For a Mobile Platform por Vidal, Anna, Talens, Pau, Prats-Montalbán, José M., Cubero, Sergio, Albert, Francisco, Blasco, José

    Publicado 2017
    “…Recently, a mobile platform that incorporates a computer vision system capable of pre-sorting the fruit while it is being harvested has been developed as an aid in the harvesting task. …”
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  2. Advancing wetland mapping in Argentina: a probalitistic approach integrating remote sensing, machine learning, and cloud computing towards sustainable ecosystem monitoring por Navarro, María Fabiana, Calamari, Noelia Cecilia, Navarro, Carlos Saúl, Enriquez, Andrea Soledad, Mosciaro, Maria Jesus, Saucedo, Griselda Isabel, Barrios, Raúl Ariel, Curcio, Matías Hernán, Dieta, Victorio, Garcia Martinez, Guillermo Carlos, Iturralde Elortegui, Maria Del Rosario Ma, Michard, Nicole Jacqueline, Paredes, Paula Natalia, Umaña, Fernando, Alday Poblete, Silvina Esther, Pezzola, Nestor Alejandro, Vidal, Claudia, Winschel, Cristina Ines, Albarracin Franco, Silvia, Behr, Santiago Javier, Cianfagna, Francisco A., Cremona, Maria Victoria, Alvarenga, Fernando Agustin, Perucca, Alba Ruth, Lopez, Astor Emilio, Miranda, Federico Waldemar, Kurtz, Ditmar Bernardo

    Publicado 2025
    “…This study addresses these challenges by presenting a probabilistic wetland distribution map for Argentina, inte­ grating 20 years of satellite imagery with machine learning and cloud computing technologies. Our approach introduces a comprehensive set of biophysical indices, enabling the identification of key wetland characteristics: 1) permanent or temporal surface water presence; 2) water-adapted vegetation phenology; and 3) geo­ morphology conducive to water accumulation. …”
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  3. Differentiating nutritional and water statuses in Hass avocado plantations through a temporal analysis of vegetation indices computed from aerial RGB images por Salazar Reque, Itamar, Arteaga, Daniel, Mendoza, Fabiola, Rojas Meza, María Elena, Soto Jeri, Jonell, Huaman, Samuel, Kemper, Guillermo

    Publicado 2023
    “…We used an image processing workflow consisting of image selection through a convolutional neural network (CNN) model, tree crown segmentation, color correction and feature extraction to automate the computation of VIs from RGB images. To compare the performance of VIs in the differentiation of nutritional and water statuses, we proposed a comparison metric called Mean Distance between Vegetation Indices (MDVI), analyzed the evolution of the extracted features, and studied their relationships with gold standard Normalized Difference Vegetation Index (NDVI) measurements. …”
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