Národní úložiště šedé literatury Nalezeno 1 záznamů.  Hledání trvalo 0.01 vteřin. 
Graph Neural Networks for Document Analysis
Patrik, Nikolas ; Španěl, Michal (oponent) ; Hradiš, Michal (vedoucí práce)
In this thesis we use for graph neural networks for document analysis. In the beggining we introduce how these graph convolutional networks work and also we introduce concept which is used for their implementation. Next, we explain current solution that solves semantic labeling of text entities in scanned documents, what is also same as the goal of this thesis. In following chapter we present solution which should be used for the mentioned problem as well as another problem which is extraction of specific data using active learning. Gradually, we explain how this solution was implemented and what tools we have used. Before ending, we show our dataset, we have annotated and we meant to use for evaluation and training of our solution. In the end, we present results of this thesis, compare our model with others and also evaluate how our model was able to extract specified data using active learning.

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