Name
Abstract | ||
|---|---|---|
Recurrent Neural Networks (RNNs) and their more recent variant Long Short-Term Memory (LSTM) are utilised in a number of modern applications like Natural Language Processing and human action recognition, where capturing longterm dependencies on sequential and temporal data is required. However, their computational structure imposes a challenge when it comes to their efficient mapping on a computin... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICFPT51103.2020.00010 | 2020 International Conference on Field-Programmable Technology (ICFPT) |
Keywords | DocType | ISBN |
Performance evaluation,Recurrent neural networks,Processor scheduling,Computational modeling,Memory management,Predictive models,Natural language processing | Conference | 978-1-6654-2302-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefano Ribes | 1 | 0 | 0.34 |
| Pedro Trancoso | 2 | 377 | 43.79 |
| Ioannis Sourdis | 3 | 456 | 44.17 |
| Christos-Savvas Bouganis | 4 | 37 | 7.60 |