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Found 3 papers, 1 papers with code
Bridging Human Concepts and Computer Vision for Explainable Face Verification
With Artificial Intelligence (AI) influencing the decision-making process of sensitive applications such as Face Verification, it is fundamental to ensure the transparency, fairness, and accountability of decisions.
Transforming gradient-based techniques into interpretable methods
The explication of Convolutional Neural Networks (CNN) through xAI techniques often poses challenges in interpretation.
Unsupervised discovery of Interpretable Visual Concepts
Attribution maps from xAI techniques, such as Integrated Gradients, are a typical example of a visualization technique containing a high level of information, but with difficult interpretation.
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