Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence

George K Thiruvathukal; Yung-Hisang Lu; Jaeyoun Kim; Yiran Chen; Bo Chen

Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence

George K Thiruvathukal, Yung-Hisang Lu, Jaeyoun Kim, Yiran Chen, Bo Chen

Department of Computer Science

Research output: Book/Report › Book

Abstract

Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.

Original language	American English
State	Published - Feb 1 2022

Keywords

computer vision
low power
energy efficient
battery power
competitions

Disciplines

Computer Sciences

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Low-Power Computer Vision Improve the Efficiency of Artificial IFinal published version, 4.45 MBLicense: Unspecified

https://www.taylorfrancis.com/books/edit/10.1201/9781003162810/low-power-computer-vision-george-thiruvathukal-yung-hsiang-lu-jaeyoun-kim-yiran-chen-bo-chen

Cite this

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title = "Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence",

abstract = " Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.",

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author = "Thiruvathukal, \{George K\} and Yung-Hisang Lu and Jaeyoun Kim and Yiran Chen and Bo Chen",

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AU - Chen, Bo

N1 - Thiruvathukal, G.K., Lu, Y.-H., Kim, J., Chen, Y., & Chen, B. (Eds.). (2022). Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781003162810

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Y1 - 2022/2/1

N2 - Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.

AB - Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.

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KW - low power

KW - energy efficient

KW - battery power

KW - competitions

UR - https://ecommons.luc.edu/cs_facpubs/281

M3 - Book

BT - Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence

ER -

Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence

Abstract

Keywords

Disciplines

Access to Document

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Cite this