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2018 Low-Power Image Recognition Challenge

Authors :
Alyamkin, Sergei
Ardi, Matthew
Brighton, Achille
Berg, Alexander C.
Chen, Yiran
Cheng, Hsin-Pai
Chen, Bo
Fan, Zichen
Feng, Chen
Fu, Bo
Gauen, Kent
Go, Jongkook
Goncharenko, Alexander
Guo, Xuyang
Nguyen, Hong Hanh
Howard, Andrew
Huang, Yuanjun
Kang, Donghyun
Kim, Jaeyoun
Kondratyev, Alexander
Lee, Seungjae
Lee, Suwoong
Lee, Junhyeok
Liang, Zhiyu
Liu, Xin
Liu, Juzheng
Li, Zichao
Lu, Yang
Lu, Yung-Hsiang
Malik, Deeptanshu
Park, Eunbyung
Repin, Denis
Sheng, Tao
Shen, Liang
Sun, Fei
Svitov, David
Thiruvathukal, George K.
Zhang, Baiwu
Zhang, Jingchi
Zhang, Xiaopeng
Zhuo, Shaojie
Publication Year :
2018
Publisher :
arXiv, 2018.

Abstract

The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technologies that can classify and detect objects in images efficiently (short execution time and low energy consumption) and accurately (high precision). Over the four years, the winners' scores have improved more than 24 times. As computer vision is widely used in many battery-powered systems (such as drones and mobile phones), the need for low-power computer vision will become increasingly important. This paper summarizes LPIRC 2018 by describing the three different tracks and the winners' solutions.<br />Comment: 13 pages, workshop in 2018 CVPR, competition, low-power, image recognition

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....a4d0d6d6f55649728dbd0754ff11820f
Full Text :
https://doi.org/10.48550/arxiv.1810.01732