Fast Object Detection at Constrained Energy
文献类型：期刊论文
| 作者 | Jingyu Liu1 ; Yongzhen Huang1; Junran Peng1; Jun Yao2; Liang Wang1
|
| 刊名 | IEEE Trans. on Emerging Topics in Computing
 |
| 出版日期 | 2016 |
| 期号 | 1-1页码:99 |
| 关键词 | Object Detection Constrained Energy Fast-rcnn |
| 英文摘要 |
Visual computing, e.g., automatic object detection, in mobile
devices attracts more and more attention recently, in which fast models
at constrained energy cost is a critical problem. In this paper, we
introduce our work on designing models based on deep learning for
200 classes object detection in mobile devices, as well as exploring
trade-off between accuracy and energy cost. In particular, we investigate
several methods of extracting object proposals and integrate them into
the fast-RCNN framework for object detection. Extensive experiments
are conducted using the Jetson TK1 SOC platform and the Alienware-15 laptop, including detailed parameters evaluation with respect to
accuracy, energy cost and speed. From these experiments, we conclude
how to obtain good balance between accuracy and energy cost, which
might provide guidance to design effective and efficient object detection
models on mobile devices. |
| WOS记录号 | WOS:000443894400010 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19701]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 作者单位 | 1.中科院自动化所 2.华为有限公司 |
| 推荐引用方式 GB/T 7714 | Jingyu Liu,Yongzhen Huang,Junran Peng,et al. Fast Object Detection at Constrained Energy[J]. IEEE Trans. on Emerging Topics in Computing,2016(1-1):99. |
| APA | Jingyu Liu,Yongzhen Huang,Junran Peng,Jun Yao,&Liang Wang.(2016).Fast Object Detection at Constrained Energy.IEEE Trans. on Emerging Topics in Computing(1-1),99. |
| MLA | Jingyu Liu,et al."Fast Object Detection at Constrained Energy".IEEE Trans. on Emerging Topics in Computing .1-1(2016):99. |
入库方式： OAI收割
来源：自动化研究所
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