Name
Title | ||
|---|---|---|
An Fpga Implementation Of Convolutional Spiking Neural Networks For Radioisotope Identification |
Abstract | ||
|---|---|---|
This paper details FPGA implementation methodology for Convolutional Spiking Neural Networks (CSNN) and applies this methodology to low-power radioisotope identification using high resolution data. A power consumption of 75 mW has been achieved on an FPGA implementation of a CSNN, with the inference accuracy of 90.62% on a synthetic dataset. The chip validation method is presented. Prototyping was accelerated by evaluating SNN parameters using SpiNNaker neuromorphic platform. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISCAS51556.2021.9401412 | 2021 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) |
Keywords | DocType | ISSN |
event-based signal processing, low power, radioisotope identification, convolutional spiking neural networks, FPGA, SpiNNaker | Conference | 0271-4302 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
10 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoyu Huang | 1 | 0 | 0.34 |
| Edward Jones | 2 | 0 | 1.01 |
| Siru Zhang | 3 | 0 | 0.34 |
| Shouyu Xie | 4 | 0 | 0.34 |
| Steve Furber | 5 | 5 | 1.82 |
| Yannis Goulermas | 6 | 0 | 1.35 |
| Edward Marsden | 7 | 0 | 0.34 |
| Ian Baistow | 8 | 0 | 0.34 |
| Srinjoy Mitra | 9 | 0 | 0.34 |
| Alister Hamilton | 10 | 117 | 19.02 |