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CNN-DST: ensemble deep learning based on Dempster-Shafer theory for
  vibration-based fault recognition

CNN-DST: ensemble deep learning based on Dempster-Shafer theory for vibration-based fault recognition

14 October 2021
V. Yaghoubi
Liangliang Cheng
W. Van Paepegem
M. Kersemans
ArXivPDFHTML

Papers citing "CNN-DST: ensemble deep learning based on Dempster-Shafer theory for vibration-based fault recognition"

2 / 2 papers shown
Title
Feature Fusion for Improved Classification: Combining Dempster-Shafer
  Theory and Multiple CNN Architectures
Feature Fusion for Improved Classification: Combining Dempster-Shafer Theory and Multiple CNN Architectures
Ayyub Alzahem
W. Boulila
Maha Driss
Anis Koubaa
25
2
0
23 May 2024
Convolutional generative adversarial imputation networks for
  spatio-temporal missing data in storm surge simulations
Convolutional generative adversarial imputation networks for spatio-temporal missing data in storm surge simulations
Ehsan Adeli
Jize Zhang
A. Taflanidis
AI4TS
AI4CE
GAN
34
3
0
03 Nov 2021
1