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Found 4 papers, 4 papers with code
SuSi: Supervised Self-Organizing Maps for Regression and Classification in Python
In this paper, we introduce the freely available Supervised Self-organizing maps (SuSi) Python package which performs supervised regression and classification.
Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data
In future work, we can further enhance the introduced LucasCNN, LucasResNet and LucasCoordConv and include additional variables of the rich LUCAS dataset.
Developing a machine learning framework for estimating soil moisture with VNIR hyperspectral data
In this paper, we investigate the potential of estimating the soil-moisture content based on VNIR hyperspectral data combined with LWIR data.
Fusion of hyperspectral and ground penetrating radar to estimate soil moisture
In the first approach, simulated GPR data is generated either by an interpolation along the time axis or by a machine learning model.
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