2018 Low-Power Image Recognition Challenge

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 acc...

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Published in:arXiv.org 2018-10
Main Authors: Alyamkin, Sergei, Ardi, Matthew, Brighton, Achille, Berg, Alexander C, Chen, Yiran, Hsin-Pai, Cheng, Chen, Bo, Fan, Zichen, Chen, Feng, 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
Format: Article
Language:English
Subjects:
Batteries
Cameras
Competition
Computer vision
Energy consumption
Image classification
Image detection
Object recognition
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container_title arXiv.org
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creator Alyamkin, Sergei
Ardi, Matthew
Brighton, Achille
Berg, Alexander C
Chen, Yiran
Hsin-Pai, Cheng
Chen, Bo
Fan, Zichen
Chen, Feng
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
description 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.
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subjects Batteries
Cameras
Competition
Computer vision
Energy consumption
Image classification
Image detection
Object recognition
title 2018 Low-Power Image Recognition Challenge
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