Skip to content
/ E-FCN Public
forked from tongzheng1992/E-FCN

This is the available code for the paper `evidential fully convolutional network for semantic segmentation (arXiv preprint arXiv:2103.13544)

License

Notifications You must be signed in to change notification settings

tasavat/E-FCN

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

E-FCN

This is the avaiable code for the paper "Evidential fully convolutional network for semantic segmentation" (arXiv:2103.13544).

Codes for Dempster-Shafer layer, pignistic transformation layer and utility layer are in the file "libs".

The file "E-Unet.ipynb" provides a demo about how to build, train, and interfere precise and imprecise segmantation with evidential FCN models. The file "Metrics.ipynb" provides a demo about how to compute PU, UIoU and ECE with a ready-trained evidential FCN model.

The file "weights_zoo" includes the parameters of two trained evidential FCN models that are used in the demo.

The required libraries and their version:

python == 3.7.10

tensorflow == 2.4.1.

About

This is the available code for the paper `evidential fully convolutional network for semantic segmentation (arXiv preprint arXiv:2103.13544)

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 99.2%
  • Python 0.8%