Name
Abstract | ||
|---|---|---|
The recent technology advancement on unmanned aerial vehicle (UAV) has enabled diverse applications in vision-related outdoor tasks. Visual object detection is a crucial task among them. However, it is difficult to actually deploy detectors on embedded devices due to the challenges among energy consumption, accuracy, and speed. In this article, we address a few key challenges from the platform, application to the system, and propose an energy-efficient system for real-time UAV object detection on an embedded platform. The proposed system can achieve speed of 28.5 FPS and 2.7-FPS/W energy efficiency on the data set from 2018 low-power object detection challenges (LPODCs). |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCAD.2019.2957724 | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Keywords | DocType | Volume |
Feature extraction,Object detection,Detectors,Real-time systems,Training,Task analysis,Unmanned aerial vehicles | Journal | 39 |
Issue | ISSN | Citations |
10 | 0278-0070 | 2 |
PageRank | References | Authors |
0.38 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianing Deng | 1 | 2 | 0.72 |
| Zhiguo Shi | 2 | 246 | 26.13 |
| Cheng Zhuo | 3 | 239 | 28.01 |