Name
Title | ||
|---|---|---|
Live Demonstration: Feature Extraction System Using Restricted Boltzmann Machines On Fpga |
Abstract | ||
|---|---|---|
Real-time results obtained from an unsupervised feature extraction system using Restricted Boltzmann Machines (RBMs) implemented on FPGA are presented. The feature extraction application is demonstrated using the MNIST dataset, and the weights storing features are visualized in real-time. A digit classification is also performed based on the learning results. Our demonstration system performs 134 times faster than the compared conventional CPU. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | Boltzmann machine,MNIST database,Computer science,Field-programmable gate array,Electronic engineering,Feature extraction,Computational science,Computer hardware |
DocType | ISSN | Citations |
Conference | 0271-4302 | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kodai Ueyoshi | 1 | 3 | 1.65 |
| Takao Marukame | 2 | 4 | 2.69 |
| Tetsuya Asai | 3 | 79 | 26.75 |
| Masato Motomura | 4 | 8 | 3.65 |
| Alexandre Schmid | 5 | 19 | 2.19 |