Three Years of Low‐Power Image Recognition Challenge: Introduction to Special Session
Kent Gauen1,a, Ryan Dailey1,b, Yung-Hsiang Lu1,c, Eunbyung Park2,d, Wei Liu2,e, Alexander C. Berg2,f and Yiran Chen3
1Purdue University, West Lafayette, Indiana, USA
agauenk@purdue.edu
bdailey1@purdue.edu
cyunglu@purdue.edu
2University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
deunbyung@cs.unc.edu
ewliu@cs.unc.edu
faberg@cs.unc.edu
3Duke University, Durham, North Carolina, USA
yiran.chen@duke.edu
ABSTRACT
Reducing power consumption has been one of the most important goals since the creation of electronic systems. Energy efficiency is increasingly important as battery‐powered systems (such as smartphones, drones, and body cameras) are widely used. It is desirable using the on‐board computers to recognize objects in the images captured by these cameras. The Low‐Power Image Recognition Challenge (LPIRC) is an annual competition started in 2015. The special session includes presentations given by the winners of the first three years of LPIRC. This paper explains the rules of the competition and the rationale, summarizes the teams’ scores, and describes the lessons learned in the first three years. The paper suggests possible improvements of future challenges.
Keywords: Low‐Power Electronics, Computer Vision, Machine Intelligence.
