Name
Abstract | ||
|---|---|---|
We exploit the dense structure of nuclei to postulate that in such clusters, the neuronal cells will communicate via soma-to-soma interactions, aswell as through synapses. Using the mathematical structure of the spiking Random Neural Network, we construct a multi-layer architecture for Deep Learning. An efficient training procedure is proposed for this architecture. It is then specialized to multi-channel datasets, and applied to images and sensor-based data. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-67792-7_1 | MAN-MACHINE INTERACTIONS 5, ICMMI 2017 |
Keywords | DocType | Volume |
Deep learning,Neural network,Machine learning | Conference | 659 |
ISSN | Citations | PageRank |
2194-5357 | 1 | 0.36 |
References | Authors | |
12 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erol Gelenbe | 1 | 4948 | 893.77 |
| Yonghua Yin | 2 | 69 | 7.58 |