Concepedia

Artificial neural networks on integrated multispectral and SAR data for high-performance prediction of eucalyptus biomass

Getúlio Fonseca Domingues, Vicente Paulo Soares, Hélio Garcia Leite, Antônio Santana Ferraz, Carlos Antônio Álvares Soares Ribeiro, Alexandre Simões Lorenzon, Gustavo Eduardo Marcatti, Thaisa Ribeiro Teixeira, Nero Lemos Martins de Castro, Pedro Henrique Santos Mota,

Computers and Electronics in Agriculture · 2019 · 33 citations · 26 references

Concepts

Precision AgricultureEnvironmental MonitoringEucalyptus BiomassData ScienceSynthetic Aperture RadarArtificial Neural NetworksEngineeringForestryRemote SensingTerrestrial SensingForecastingEarth Observation DataSar DataEarth ScienceHyperspectral ImagingForest Biomass

References

26

Multilayer feedforward networks are universal approximators

Kurt Hornik, Maxwell B. Stinchcombe, Halbert White · Neural Networks · 1989 · 20.7K citations

Evolving Neural Network, Engineering, Machine Learning +5

Multilayer feedforward networks are universal approximators

HornikK., StinchcombeM., WhiteH. · Neural Networks · 1989 · 9.3K citations

Evolving Neural Network, Engineering, Machine Learning +5

The Problem of Overfitting

Douglas M. Hawkins · Journal of Chemical Information and Computer Sciences · 2003 · 2.4K citations

Artificial Intelligence, Engineering, Machine Learning +20

Relating forest biomass to SAR data

Thuy Le Toan, Amélie Beaudoin, J. Riom et al. · IEEE Transactions on Geoscience and Remote Sensing · 1992 · 812 citations

Engineering, Forest Biometrics, Land Use +20

Neural network studies. 1. Comparison of overfitting and overtraining

Igor V. Tetko, David J. Livingstone, Alexander I. Luik · Journal of Chemical Information and Computer Sciences · 1995 · 667 citations

Engineering, Machine Learning, Media Standards +18