Mobiprox: Supporting Dynamic Approximate Computing on Mobiles
Author:
Affiliation:
1. Cosylab, Ljubljana, Slovenia
2. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
3. Department of Computer Science, University of Illinois at Urbana-Champaign, Champaign, IL, USA
Funder
Slovenian Research Agency through the Bringing Resource Efficiency to Smartphones With Approximate Computing Project
Context-Aware On-Device Approximate Computing project
Research Programmes
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6488907/10508620/10436434.pdf?arnumber=10436434
Reference49 articles.
1. A First Look at Deep Learning Apps on Smartphones
2. MobileNets: Efficient convolutional neural networks for mobile vision applications;Howard;arXiv:1704.04861,2017
3. EfficientNet: Rethinking model scaling for convolutional neural networks;Tan
4. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
5. EmBench
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