A novel constrained dense convolutional autoencoder and DNN-based semi-supervised method for shield machine tunnel geological formation recognition

Title
A novel constrained dense convolutional autoencoder and DNN-based semi-supervised method for shield machine tunnel geological formation recognition
Authors
Keywords
Geological formation recognition, Shield machine, Semi-supervised learning, Constrained dense convolutional autoencoder, Parameter selection
Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 165, Issue -, Pages 108353
Publisher
Elsevier BV
Online
2021-08-27
DOI
10.1016/j.ymssp.2021.108353

Ask authors/readers for more resources

Reprint

Contact the author

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Find the ideal target journal for your manuscript

Explore over 38,000 international journals covering a vast array of academic fields.

Search