Number of necessary training examples for Neural Networks with different number of trainable parameters

In this work, the network complexity should be reduced with a concomitant reduction in the number of necessary training examples. The focus thus was on the dependence of proper evaluation metrics on the number of adjustable parameters of the considered deep neural network. The used data set encompas...

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Detalles Bibliográficos
Autores principales: Götz, Th.I., Göb, S., Sawant, S., Erick, X.F., Wittenberg, T., Schmidkonz, C., Tomé, A.M., Lang, E.W., Ramming, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577052/
https://www.ncbi.nlm.nih.gov/pubmed/36268092
http://dx.doi.org/10.1016/j.jpi.2022.100114

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577052/
https://www.ncbi.nlm.nih.gov/pubmed/36268092
http://dx.doi.org/10.1016/j.jpi.2022.100114

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