Search Results - "Schons, Cristine"

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  1. 1

    Simulating Araucaria angustifolia (Bertol.) Kuntze Timber Stocks With Liocourt’s Law in a Natural Forest in Southern Brazil by Emanuel Arnoni Costa, Veraldo Liesenberg, André Felipe Hess, César Augusto Guimarães Finger, Paulo Renato Schneider, Régis Villanova Longhi, Cristine Tagliapietra Schons, Geedre Adriano Borsoi

    Published in Forests (01-03-2020)
    “…This paper presents a simulation of the regulation of Araucaria angustifolia (Bertol.) Kuntze timber stocks using Liocourt's law. Although this species is…”
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    Journal Article
  2. 2

    Using crown characterisation variables as indicators of the vigour, competition and growth of Brazilian pine by Barbosa, Lorena Oliveira, Finger, César Augusto Guimarães, Costa, Emanuel Arnoni, Campoe, Otávio Camargo, Schons, Cristine Tagliapietra

    Published in Southern forests (02-10-2021)
    “…Crown variables are used in growth and production models to increase the accuracy of estimates. These variables are costly and difficult to measure, mainly in…”
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  3. 3

    Individual Tree Basal Area Increment Models for Brazilian Pine (Araucaria angustifolia) Using Artificial Neural Networks by Lorena Oliveira Barbosa, Emanuel Arnoni Costa, Cristine Tagliapietra Schons, César Augusto Guimarães Finger, Veraldo Liesenberg, Polyanna da Conceição Bispo

    Published in Forests (01-07-2022)
    “…This research aimed to develop statistical models to predict basal area increment (BAI) for Araucaria angustifolia using Artificial Neural Networks (ANNs)…”
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    Journal Article
  4. 4

    Enhancing Height Predictions of Brazilian Pine for Mixed, Uneven-Aged Forests Using Artificial Neural Networks by Emanuel Arnoni Costa, André Felipe Hess, César Augusto Guimarães Finger, Cristine Tagliapietra Schons, Danieli Regina Klein, Lorena Oliveira Barbosa, Geedre Adriano Borsoi, Veraldo Liesenberg, Polyanna da Conceição Bispo

    Published in Forests (01-08-2022)
    “…Artificial intelligence (AI) seeks to simulate the human ability to reason, make decisions, and solve problems. Several AI methodologies have been introduced…”
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    Journal Article
  5. 5

    Understanding bark thickness variations for Araucaria angustifolia in southern Brazil by Costa, Emanuel Arnoni, Liesenberg, Veraldo, Finger, César Augusto Guimarães, Hess, André Felipe, Schons, Cristine Tagliapietra

    Published in Journal of forestry research (01-06-2021)
    “…This study aimed to understand bark thickness variations of Araucaria angustifolia (Bertol.) Kuntze trees growing in natural forest remnants in southern…”
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  6. 6

    Estimated flooded rice grain yield and nitrogen content in leaves based on RPAS images and machine learning by Eugenio, Fernando Coelho, Grohs, Mara, Schuh, Mateus, Venancio, Luan Peroni, Schons, Cristine, Badin, Tiago Luis, Mallmann, Caroline Lorenci, Fernandes, Pablo, Pereira da Silva, Sally Deborah, Fantinel, Roberta Aparecida

    Published in Field crops research (01-03-2023)
    “…Remote sensing based on Remote Piloted Aircraft Systems (RPAS) has proved valuable for monitoring agronomic parameters in precision agriculture. This research…”
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    COMPARAÇÃO ENTRE DIFERENTES MÉTODOS PARA ESTIMATIVA VOLUMÉTRICA DE ESPÉCIES COMERCIAIS DA AMAZÔNIA by Lanssanova, Luciano Rodrigo, Alba da Silva, Franciele, Tagliapietra Schons, Cristine, Da Silva Pererira, Ane Caroline

    Published in Biofix Scientific Journal (15-03-2018)
    “…A floresta Amazônica apresenta espécies de elevado potencial para exploração sustentável de madeira, entretanto, para que sejam exploradas, há a necessidade de…”
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    Journal Article
  9. 9

    Estimation of soybean yield from machine learning techniques and multispectral RPAS imagery by Eugenio, Fernando Coelho, Grohs, Mara, Venancio, Luan Peroni, Schuh, Mateus, Bottega, Eduardo Leonel, Ruoso, Régis, Schons, Cristine, Mallmann, Caroline Lorenci, Badin, Tiago Luis, Fernandes, Pablo

    Published in Remote sensing applications (01-11-2020)
    “…Throughout the plant development, the physiological processes of growth, as well as the handling of water and fertilizers represent sources of variation in the…”
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  10. 10
  11. 11

    Flooded rice variables from high-resolution multispectral images and machine learning algorithms by Eugenio, Fernando Coelho, Grohs, Mara, Schuh, Mateus Sabadi, Venancio, Luan Peroni, Schons, Cristine, Badin, Tiago Luis, Mallmann, Caroline Lorenci, Fernandes, Pablo, Pereira da Silva, Sally Deborah, Fantinel, Roberta Aparecida

    Published in Remote sensing applications (01-08-2023)
    “…Remote spectral detection via orbital, aerial or terrestrial platforms is considered a valuable tool for non-destructive real-time estimation of the Leaf Area…”
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  12. 12

    EFEITO DO NÚMERO DE NEURÔNIOS NA CAMADA OCULTA PARA RELAÇÕES HIPSOMÉTRICAS DE EUCALIPTO USANDO REDES NEURAIS ARTIFICIAIS by Bueno, Gabriel Fernandes, Costa, Emanuel Arnoni, Cristina, Amanda Nunes, Soares, Alvaro Augusto Vieira, De Miranda, Rodrigo Otávio Veiga, Schons, Cristine Tagliapietra

    Published in Biofix Scientific Journal (02-07-2020)
    “…As redes neurais artificiais têm mostrado performance melhor ou pelo menos similar à dos modelos tradicionais de regressão usados a modelagem florestal. No…”
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    Journal Article