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Found 4 papers, 2 papers with code
A comprehensive study on fidelity metrics for XAI
We applied our benchmark to assess the existing fidelity metrics in two different experiments, each using public datasets comprising 52, 000 images.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
A novel approach to generate datasets with XAI ground truth to evaluate image models
With the increased usage of artificial intelligence (AI), it is imperative to understand how these models work internally.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Sickle-cell disease diagnosis support selecting the most appropriate machinelearning method: Towards a general and interpretable approach for cellmorphology analysis from microscopy images
We also defined how to select the most important features for classification to decrease the complexity and the training time, and for interpretability purpose in opaque models.
Modelling depth for nonparametric foreground segmentation using RGBD devices
In order to unify all the device channel cues, a new probabilistic depth data model is also proposed where we show how handle the inaccurate data to improve foreground segmentation.
