CHAKRABORTY, Megha, LI, Wei, FABER, Johannes, RÜMPKER, Georg, STÖCKER, Horst und SRIVASTAVA, Nishtha, [no date]. A study on the effect of input data length on a deep-learning-based magnitude classifier. Preprint. Frankfurt am Main: Universitätsbibliothek Johann Christian Senckenberg.
Elsevier - Harvard (with titles)Chakraborty, M., Li, W., Faber, J., Rümpker, G., Stöcker, H., Srivastava, N., o. J. A study on the effect of input data length on a deep-learning-based magnitude classifier, Preprint. ed. Universitätsbibliothek Johann Christian Senckenberg, Frankfurt am Main. https://doi.org/10.48550/ar Xiv.2112.07551
American Psychological Association 7th editionChakraborty, M., Li, W., Faber, J., Rümpker, G., Stöcker, H., & Srivastava, N. (o. J.). A study on the effect of input data length on a deep-learning-based magnitude classifier (Preprint) [Cd]. Universitätsbibliothek Johann Christian Senckenberg. https://doi.org/10.48550/ar Xiv.2112.07551
Springer - Basic (author-date)Chakraborty M, Li W, Faber J, Rümpker G, Stöcker H, Srivastava N A study on the effect of input data length on a deep-learning-based magnitude classifier, Preprint. Universitätsbibliothek Johann Christian Senckenberg, Frankfurt am Main
Juristische Zitierweise (Stüber) (Deutsch)Chakraborty, Megha/ Li, Wei/ Faber, Johannes/ Rümpker, Georg/ Stöcker, Horst/ Srivastava, Nishtha, A study on the effect of input data length on a deep-learning-based magnitude classifier, Preprint , Frankfurt am Main .