Efficient Computer Vision for Embedded Systems

George K. Thiruvathukal; Yung Hsiang Lu

doi:/MC.2022.3145677

Efficient Computer Vision for Embedded Systems

George K. Thiruvathukal, Yung Hsiang Lu

Department of Computer Science

Purdue University

Research output: Contribution to specialist publication › Article

Abstract

The winners, as well as the organizers and sponsors of the IEEE Low-Power Computer Vision Challenge, share their insights into making computer vision (CV) more efficient for running on mobile or embedded systems. As CV (and more generally, artificial intelligence) is deployed widely on the Internet of Things, efficiency will become increasingly important.

Original language	English
Pages	15-19
Number of pages	5
Volume	55
No	4
Specialist publication	Computer
DOIs	https://doi.org//MC.2022.3145677 https://doi.org/10.1109/MC.2022.3145677
State	Published - Apr 1 2022

ASJC Scopus Subject Areas

General Computer Science

Keywords

computer vision
computer systems
low-power
interview
roundtable

Disciplines

Artificial Intelligence and Robotics
Computer Sciences

Access to Document

/MC.2022.3145677License: Unspecified
10.1109/MC.2022.3145677

https://ieeexplore.ieee.org/document/9755195

Cite this

@misc{e04b6d9ea90a4bd39e2dd42188258c83,

title = "Efficient Computer Vision for Embedded Systems",

abstract = " The winners, as well as the organizers and sponsors of the IEEE Low-Power Computer Vision Challenge, share their insights into making computer vision (CV) more efficient for running on mobile or embedded systems. As CV (and more generally, artificial intelligence) is deployed widely on the Internet of Things, efficiency will become increasingly important.",

keywords = "computer vision, computer systems, low-power, interview, roundtable",

author = "Thiruvathukal, \{George K.\} and Lu, \{Yung Hsiang\}",

note = "G. K. Thiruvathukal and Y.-H. Lu, {"}Efficient Computer Vision for Embedded Systems,{"} in Computer, vol. 55, no. 4, pp. 15-19, April 2022, doi: 10.1109/MC.2022.3145677",

year = "2022",

month = apr,

day = "1",

doi = "/MC.2022.3145677",

language = "English",

volume = "55",

pages = "15--19",

journal = "Computer",

issn = "0018-9162",

}

TY - GEN

T1 - Efficient Computer Vision for Embedded Systems

AU - Thiruvathukal, George K.

AU - Lu, Yung Hsiang

N1 - G. K. Thiruvathukal and Y.-H. Lu, "Efficient Computer Vision for Embedded Systems," in Computer, vol. 55, no. 4, pp. 15-19, April 2022, doi: 10.1109/MC.2022.3145677

PY - 2022/4/1

Y1 - 2022/4/1

N2 - The winners, as well as the organizers and sponsors of the IEEE Low-Power Computer Vision Challenge, share their insights into making computer vision (CV) more efficient for running on mobile or embedded systems. As CV (and more generally, artificial intelligence) is deployed widely on the Internet of Things, efficiency will become increasingly important.

AB - The winners, as well as the organizers and sponsors of the IEEE Low-Power Computer Vision Challenge, share their insights into making computer vision (CV) more efficient for running on mobile or embedded systems. As CV (and more generally, artificial intelligence) is deployed widely on the Internet of Things, efficiency will become increasingly important.

KW - computer vision

KW - computer systems

KW - low-power

KW - interview

KW - roundtable

UR - https://ecommons.luc.edu/cs_facpubs/286

UR - https://ieeexplore.ieee.org/document/9755195

U2 - /MC.2022.3145677

DO - /MC.2022.3145677

M3 - Article

SN - 0018-9162

VL - 55

SP - 15

EP - 19

JO - Computer

JF - Computer

ER -

Efficient Computer Vision for Embedded Systems

Abstract

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

Other files and links

Cite this