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Book
Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence
Computer Science: Faculty Publications and Other Works
  • George K Thiruvathukal, Loyola University Chicago
  • Yung-Hisang Lu, Purdue University
  • Jaeyoun Kim, Google
  • Yiran Chen, Duke University
  • Bo Chen
Document Type
Book
Publication Date
2-1-2022
Publisher Name
Taylor and Francis / Chapman and Hall / CRC Press
Publisher Location
New York
Disciplines
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.

Identifier
10.1201/9781003162810
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Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 3.0
Citation Information
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