Low-Power Computer Vision : Improve the Efficiency of Artificial Intelligence Hardback
Edited by George K. (Loyola University Chicago, Chicago, Illinois) Thiruvathukal, Yung-Hsiang Lu, Jaeyoun Kim, Yiran Chen, Bo Chen
Part of the Chapman & Hall/CRC Computer Vision series
Hardback
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Description
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.
Information
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In Stock - low on stock, only 1 copy remainingFree UK DeliveryEstimated delivery 2-3 working days
- Format:Hardback
- Pages:436 pages, 58 Tables, black and white; 61 Line drawings, color; 39 Line drawings, black and white; 1
- Publisher:Taylor & Francis Ltd
- Publication Date:23/02/2022
- Category:
- ISBN:9780367744700
Information
-
In Stock - low on stock, only 1 copy remainingFree UK DeliveryEstimated delivery 2-3 working days
- Format:Hardback
- Pages:436 pages, 58 Tables, black and white; 61 Line drawings, color; 39 Line drawings, black and white; 1
- Publisher:Taylor & Francis Ltd
- Publication Date:23/02/2022
- Category:
- ISBN:9780367744700