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StressNAS: Affect State and Stress Detection Using Neural Architecture
  Search

StressNAS: Affect State and Stress Detection Using Neural Architecture Search

26 August 2021
Lam Huynh
Tri Nguyen
Thu Nguyen
Susanna Pirttikangas
Pekka Siirtola
ArXivPDFHTML

Papers citing "StressNAS: Affect State and Stress Detection Using Neural Architecture Search"

9 / 9 papers shown
Title
Neural Architecture Search without Training
Neural Architecture Search without Training
J. Mellor
Jack Turner
Amos Storkey
Elliot J. Crowley
61
384
0
08 Jun 2020
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture
  Search
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search
Xuanyi Dong
Yi Yang
135
711
0
02 Jan 2020
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
687
131,526
0
12 Jun 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
1.1K
20,837
0
17 Apr 2017
Neural Architecture Search with Reinforcement Learning
Neural Architecture Search with Reinforcement Learning
Barret Zoph
Quoc V. Le
454
5,372
0
05 Nov 2016
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOS
SSeg
738
37,846
0
20 May 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB
  model size
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
F. Iandola
Song Han
Matthew W. Moskewicz
Khalid Ashraf
W. Dally
Kurt Keutzer
150
7,482
0
24 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,878
0
10 Dec 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,348
0
04 Sep 2014
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