On the Post Hoc Explainability of Optimized Self-Organizing Reservoir Network for Action Recognition

This work proposes a novel unsupervised self-organizing network, called the Self-Organizing Convolutional Echo State Network (SO-ConvESN), for learning node centroids and interconnectivity maps compatible with the deterministic initialization of Echo State Network (ESN) input and reservoir weights,...

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Detalles Bibliográficos
Autores principales: Lee, Gin Chong, Loo, Chu Kiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914683/
https://www.ncbi.nlm.nih.gov/pubmed/35271052
http://dx.doi.org/10.3390/s22051905

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914683/
https://www.ncbi.nlm.nih.gov/pubmed/35271052
http://dx.doi.org/10.3390/s22051905

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