Cargando…
Neural Schematics as a unified formal graphical representation of large-scale Neural Network Structures
One of the major outcomes of neuroscientific research are models of Neural Network Structures (NNSs). Descriptions of these models usually consist of a non-standardized mixture of text, figures, and other means of visual information communication in print media. However, as neuroscience is an interd...
Autores principales: | Ehrlich, Matthias, Schüffny, René |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3807050/ https://www.ncbi.nlm.nih.gov/pubmed/24167490 http://dx.doi.org/10.3389/fninf.2013.00022 |
Ejemplares similares
-
Configurable analog-digital conversion using the neural engineering framework
por: Mayr, Christian G., et al.
Publicado: (2014) -
Representational Distance Learning for Deep Neural Networks
por: McClure, Patrick, et al.
Publicado: (2016) -
Network-driven design principles for neuromorphic systems
por: Partzsch, Johannes, et al.
Publicado: (2015) -
DNNBrain: A Unifying Toolbox for Mapping Deep Neural Networks and Brains
por: Chen, Xiayu, et al.
Publicado: (2020) -
Symbolic and Graphical Representation Scheme for Sensors Deployed in Large-Scale Structures
por: Park, Hyo Seon, et al.
Publicado: (2013)