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Robust Reference Frame Extraction from Unsteady 2D Vector Fields with Convolutional Neural Networks
[article]
2019
arXiv
pre-print
Robust feature extraction is an integral part of scientific visualization. In unsteady vector field analysis, researchers recently directed their attention towards the computation of near-steady reference frames for vortex extraction, which is a numerically challenging endeavor. In this paper, we utilize a convolutional neural network to combine two steps of the visualization pipeline in an end-to-end manner: the filtering and the feature extraction. We use neural networks for the extraction of
arXiv:1903.10255v1
fatcat:qvgts6zycre57c223hgsc7q7cq