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Nilton Nobuhiro Imai
Researcher at Sao Paulo State University
Publications - 85
Citations - 1657
Nilton Nobuhiro Imai is an academic researcher from Sao Paulo State University. The author has contributed to research in topics: Hyperspectral imaging & Random forest. The author has an hindex of 17, co-authored 80 publications receiving 1146 citations.
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Journal ArticleDOI
Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging
Olli Nevalainen,Eija Honkavaara,Sakari Tuominen,Niko Viljanen,Teemu Hakala,Xiaowei Yu,Juha Hyyppä,Heikki Saari,Ilkka Pölönen,Nilton Nobuhiro Imai,Antonio Maria Garcia Tommaselli +10 more
TL;DR: Results were promising, indicating that hyperspectral 3D remote sensing was operational from a UAV platform even in very difficult conditions, and are expected to provide a powerful tool for automating various environmental close-range remote sensing tasks in the very near future.
Journal ArticleDOI
Estimation of Chlorophyll-a Concentration and the Trophic State of the Barra Bonita Hydroelectric Reservoir Using OLI/Landsat-8 Images
Fernanda Sayuri Yoshino Watanabe,Enner Alcântara,Thanan Rodrigues,Nilton Nobuhiro Imai,Claudio Clemente Faria Barbosa,Luiz Rotta +5 more
TL;DR: Evaluated performance of images of the sensor Operational Land Imager onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir showed reasonable results, but their performance was likely impaired by the atmospheric correction.
Journal ArticleDOI
A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery
Lucas Prado Osco,Mauro dos Santos de Arruda,José Marcato Junior,Neemias Buceli da Silva,Ana Paula Marques Ramos,Érika Akemi Saito Moryia,Nilton Nobuhiro Imai,Danillo Roberto Pereira,José Eduardo Creste,Edson Takashi Matsubara,Jonathan Li,Wesley Nunes Gonçalves +11 more
TL;DR: The convolutional neural network approach developed to estimate the number and geolocation of citrus trees in high-density orchards is satisfactory and is an effective strategy to replace the traditional visual inspection method to determine the number of plants in orchard trees.
Proceedings ArticleDOI
Automatic shadow segmentation in aerial color images
Airton Marco Polidorio,Franklin César Flores,Nilton Nobuhiro Imai,Antonio Maria Garcia Tommaselli,Clélia Franco +4 more
TL;DR: A robust and efficient technique to segment shaded areas in aerial color images is presented here, based on the physical phenomenon of atmospheric dispersion of the sunlight most well known as the Rayleigh scattering effect.
Journal ArticleDOI
A Machine Learning Framework to Predict Nutrient Content in Valencia-Orange Leaf Hyperspectral Measurements
Lucas Prado Osco,Ana Paula Marques Ramos,Mayara Maezano Faita Pinheiro,Érika Akemi Saito Moriya,Nilton Nobuhiro Imai,Nayara Vasconcelos Estrabis,Felipe Ianczyk,Fabio Fernando de Araujo,Veraldo Liesenberg,Lúcio André de Castro Jorge,Jonathan Li,Lingfei Ma,Wesley Nunes Gonçalves,José Marcato Junior,José Eduardo Creste +14 more
TL;DR: The results indicate that, for the Valencia-orange leaves, surface reflectance data is more suitable to predict macronutrient content, while first-derivative spectra is better linked to micronutrients.