Name
Abstract | ||
|---|---|---|
This paper explores the use of Google's Edge TPU, a purpose-built ASIC designed to run AI at the edge. Our evaluations are done based on the use case application of automated cattle activity classification, which requires classification (inference) to run on energy limited embedded devices. For this application, we consider a deep neural network classifier, which traditionally has been a challenge... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/PerComWorkshops51409.2021.9431041 | 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) |
Keywords | DocType | ISBN |
Performance evaluation,Time-frequency analysis,Conferences,Neural networks,Cows,Energy efficiency,Data models | Conference | 978-1-6654-0424-2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seyedehfaezeh Hosseininoorbin | 1 | 0 | 0.34 |
| S. layeghy | 2 | 2 | 1.54 |
| Brano Kusy | 3 | 60 | 8.48 |
| R. Jurdak | 4 | 56 | 7.60 |
| Marius Portmann | 5 | 7 | 2.61 |