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Summary of the doctoral thesis: Study on the accuracy improvement of the grid Digital Elevaion Model using Hopfield neuron network

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The purpose of the dissertation is to test and use different accuracy assessment methods to evaluate the improvement of grid DEMs accuracy when increasing resolution by popular resampling methods. Currently and building the algorithm and programs to increase the spatial resolution and accuracy of the grid DEM using Hopfield neural networks. Objects of the study are grid DEMs which are built from different methods such as: LiDar DEM, contour and field measurements. The scope of the study includes the spatial resolution and accuracy of the above grid DEMs.

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