Paulo Eduardo Teodoro

Orcid: 0000-0002-8236-542X

According to our database1, Paulo Eduardo Teodoro authored at least 15 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
A New Approach to Identifying Sorghum Hybrids Using UAV Imagery Using Multispectral Signature and Machine Learning.
Algorithms, 2024

2023
Machine Learning in the Hyperspectral Classification of Glycaspis brimblecombei (Hemiptera Psyllidae) Attack Severity in Eucalyptus.
Remote. Sens., December, 2023

Machine Learning in the Classification of Soybean Genotypes for Primary Macronutrients' Content Using UAV-Multispectral Sensor.
Remote. Sens., March, 2023

Maize Yield Prediction with Machine Learning, Spectral Variables and Irrigation Management.
Remote. Sens., January, 2023

Changes in Carbon Dioxide Balance Associated with Land Use and Land Cover in Brazilian Legal Amazon Based on Remotely Sensed Imagery.
Remote. Sens., 2023

2022
Is the Gridded Data Accurate? Evaluation of Precipitation and Historical Wet and Dry Periods from ERA5 Data for Canadian Prairies.
Remote. Sens., December, 2022

Portable-Mechanical-Sampler System for Real-Time Monitoring and Predicting Soybean Quality in the Bulk Transport.
IEEE Trans. Instrum. Meas., 2022

Fires Drive Long-Term Environmental Degradation in the Amazon Basin.
Remote. Sens., 2022

Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian.
Remote. Sens., 2022

2021
Predicting Days to Maturity, Plant Height, and Grain Yield in Soybean: A Machine and Deep Learning Approach Using Multispectral Data.
Remote. Sens., 2021

19-year remotely sensed data in the forecast of spectral models of the environment.
Int. J. Digit. Earth, 2021

2020
Leaf Nitrogen Concentration and Plant Height Prediction for Maize Using UAV-Based Multispectral Imagery and Machine Learning Techniques.
Remote. Sens., 2020

A random forest ranking approach to predict yield in maize with uav-based vegetation spectral indices.
Comput. Electron. Agric., 2020

Mapping soybean planting area in midwest Brazil with remotely sensed images and phenology-based algorithm using the Google Earth Engine platform.
Comput. Electron. Agric., 2020

2019
Object-based image analysis supported by data mining to discriminate large areas of soybean.
Int. J. Digit. Earth, 2019


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