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An Energy-Efficient Edge Computing Paradigm for Convolution-based Image
  Upsampling

An Energy-Efficient Edge Computing Paradigm for Convolution-based Image Upsampling

15 July 2021
Ian Colbert
Ken Kreutz-Delgado
Srinjoy Das
ArXivPDFHTML

Papers citing "An Energy-Efficient Edge Computing Paradigm for Convolution-based Image Upsampling"

2 / 2 papers shown
Title
Training Deep Neural Networks with Joint Quantization and Pruning of
  Weights and Activations
Training Deep Neural Networks with Joint Quantization and Pruning of Weights and Activations
Xinyu Zhang
Ian Colbert
Ken Kreutz-Delgado
Srinjoy Das
MQ
29
11
0
15 Oct 2021
Real-Time Single Image and Video Super-Resolution Using an Efficient
  Sub-Pixel Convolutional Neural Network
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
195
5,175
0
16 Sep 2016
1