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ORCIDLeonardo Felipe Maldaner
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2020 – today
- 2021
[j6]Leonardo Felipe Maldaner
, Lucas de Paula Corrêdo, Tatiana Fernanda Canata, José Paulo Molin:
Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches. Comput. Electron. Agric. 181: 105945 (2021)- [j5]Leonardo Felipe Maldaner, José Paulo Molin, Tatiana Fernanda Canata, Maurício Martello:
A system for plant detection using sensor fusion approach based on machine learning model. Comput. Electron. Agric. 189: 106382 (2021) - [j4]Tatiana Fernanda Canata, Marcelo Chan Fu Wei, Leonardo Felipe Maldaner, José Paulo Molin:
Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique. Remote. Sens. 13(2): 232 (2021) - [j3]Lucas de Paula Corrêdo, Leonardo Felipe Maldaner, Helizani Couto Bazame, José Paulo Molin:
Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy. Sensors 21(6): 2195 (2021) - [j2]Jeovano de Jesus Alves de Lima, Leonardo Felipe Maldaner, José Paulo Molin:
Sensor Fusion with NARX Neural Network to Predict the Mass Flow in a Sugarcane Harvester. Sensors 21(13): 4530 (2021)
2010 – 2019
- 2019
- [j1]Tiago Rodrigues Tavares, Lidiane Cristina Nunes, Elton Eduardo Novais Alves, Eduardo de Almeida, Leonardo Felipe Maldaner, Francisco José Krug, Hudson Wallace Pereira de Carvalho, José Paulo Molin:
Simplifying Sample Preparation for Soil Fertility Analysis by X-ray Fluorescence Spectrometry. Sensors 19(23): 5066 (2019) - [c1]Pedro Henrique Santos, Leandro Maria Gimenez, Leonardo Felipe Maldaner, Cássio da Costa Duarte:
Performance analysis of a RADAR FMCW sensor developed for plant height measurement in agricultural and comparison with an NDVI sensor. GEOINFO 2019: 147-157
Coauthor Index
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