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Current progress and open challenges for applying deep learning …
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Machine learning for spectral properties - Nature
WebDec 29, 2024 · Here, we employ machine-learning techniques and a comprehensive set of climatic, topographic, soil, and remote sensing data to develop models capable of making predictions of soil salinity (expressed as electrical conductivity of saturated soil extract) and sodicity (measured as soil exchangeable sodium percentage) at different longitudes, … WebHere, we introduce a much simpler, though rigorous, hierarchical geometric model founded on the mean-field theory of 2D polygonal tessellations to predict extended network patterns based on molecular-level information. Based on graph theory, this approach yields pattern classification and pattern prediction within well-defined ranges. WebJan 14, 2024 · Machine-learning models have demonstrated great success in learning complex patterns that enable them to make predictions about unobserved data. In … cp -r shell