SimilarityNet: A Deep Neural Network for Similarity Analysis Within Spatio-temporal Ensembles

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dc.contributor.authorHuesmann, Karimen_US
dc.contributor.authorLinsen, Larsen_US
dc.contributor.editorBorgo, Ritaen_US
dc.contributor.editorMarai, G. Elisabetaen_US
dc.contributor.editorSchreck, Tobiasen_US
dc.date.accessioned2022-06-03T06:06:17Z
dc.date.available2022-06-03T06:06:17Z
dc.date.issued2022
dc.description.abstractLatent feature spaces of deep neural networks are frequently used to effectively capture semantic characteristics of a given dataset. In the context of spatio-temporal ensemble data, the latent space represents a similarity space without the need of an explicit definition of a field similarity measure. Commonly, these networks are trained for specific data within a targeted application. We instead propose a general training strategy in conjunction with a deep neural network architecture, which is readily applicable to any spatio-temporal ensemble data without re-training. The latent-space visualization allows for a comprehensive visual analysis of patterns and temporal evolution within the ensemble. With the use of SimilarityNet, we are able to perform similarity analyses on large-scale spatio-temporal ensembles in less than a second on commodity consumer hardware. We qualitatively compare our results to visualizations with established field similarity measures to document the interpretability of our latent space visualizations and show that they are feasible for an in-depth basic understanding of the underlying temporal evolution of a given ensemble.en_US
dc.description.number3
dc.description.sectionheadersAlgorithms and Machine Learning
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14548
dc.identifier.issn1467-8659
dc.identifier.pages379-389
dc.identifier.pages11 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14548
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14548
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleSimilarityNet: A Deep Neural Network for Similarity Analysis Within Spatio-temporal Ensemblesen_US
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