EBAnO (Explaining BlAck-box mOdels) is a wide research project focused on the explanation of Artificial Intelligence (xAI) models.
Check-out the EBAnO-Ecosystem on GitHub.EBAnO-Ecosystem
EBAnO Express is a simple and reliable explanation tool that can be used to deeply understand the reasons behind every prediction made by DCNN.
Check-out EBAnO Express on GitHub and have a look to running examples.EBAnO Express Examples
A library of explanations is available online. The explanations have been produced by EBAnO analyzing four different DCNN models:
- VGG 16
- VGG 19
- Inception V3
- Inception ResNet V2
The explanation library is available at EBAnO Explanation Library
A survey about the quality and the simplicity of understanding of the explanations produced by EBAnO is available at EBAnO Survey
PublicationsIf you find EBAnO useful in your projects or in your research you are welcome to have a look and cite our papers:
- Black-Box Model Explained Through an Assessment of Its Interpretable Features
- What's in the box? Explaining the black-box model through an evaluation of its interpretable features