Figures and details of manuscript "GAST-Net: Emission Spectroscopy Tomographic Reconstruction and Prediction with Gated Recurrent Units and Attention Mechanism"

This dataset includs the figures and details of manuscript "GAST-Net: Emission Spectroscopy Tomographic Reconstruction and Prediction with Gated Recurrent Units and Attention Mechanism"Figure 1 Schematic Diagram of CTC Imaging SystemFigure 2 GAST-Net neural network model.(a)Network model architecture (b)GRU model structure (c) Attention mechanism diagramFigure 3 GAST-Net algorithm flowchartFigure 4 Comparison between model predicted reconstructed structure and real reconstructed structure.

(a) Predicting three-dimensional structures; (b) Real three-dimensional structure; (c) Predicting two-dimensional slices of structures; (d) Real structure two-dimensional slice; (e) Quality evaluation functions for predicting and realistic structuresFigure 5 Comparison between the predicted results of the future time model and the three-dimensional structural view of real data. (a-c) Predict the reconstruction results for the first, third, and fifth moments in the future; (d-f) Traditional reconstruction results for the first, third, and fifth moments in the future; (g) Quality evaluation function of prediction and real structureFigure 6 Cross sectional comparison and difference between combustion field and real data in the future.(a)The first moment of the future;(b)The third moment of the future;(c)The fifth moment of the futureFigure 7 Quality evaluation function between prediction results of multiple time steps and real data.(a)SSIM;(b)CORR;(c)RMSE;(d)PSNRFigure 8 Compare the predicted results with the 3D structural view of the real data when inserting three frames.