FARAHAT, Amr, EFFENBERGER, Felix und VINCK, Martin, 2023. A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations. Amsterdam: Elsevier.
Elsevier - Harvard (with titles)Farahat, A., Effenberger, F., Vinck, M., 2023. A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations, Neural networks. Elsevier, Amsterdam. https://doi.org/10.1016/j.neunet.2023.08.021
American Psychological Association 7th editionFarahat, A., Effenberger, F., & Vinck, M. (ca. 2023). A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations [Cd]. In Neural networks. Elsevier. https://doi.org/10.1016/j.neunet.2023.08.021
Springer - Basic (author-date)Farahat A, Effenberger F, Vinck M (2023) A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations. Elsevier, Amsterdam
Juristische Zitierweise (Stüber) (Deutsch)Farahat, Amr/ Effenberger, Felix/ Vinck, Martin, A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations, Amsterdam 2023.