386 citations · 686 across the 16 of their papers we have counts for
3 papers · 1 filter
Explaning with trees: interpreting CNNs using hierarchies
Caroline Mazini Rodrigues, Nicolas Boutry, Laurent Najman
Challenges persist in providing interpretable explanations for neural network reasoning in explainable AI (xAI). Existing methods like Integrated Gradients produce noisy maps, and…
Bridging Human Concepts and Computer Vision for Explainable Face Verification
Miriam Doh, Caroline Mazini Rodrigues, Nicolas Boutry +3
With Artificial Intelligence (AI) influencing the decision-making process of sensitive applications such as Face Verification, it is fundamental to ensure the transparency, fairnes…
Transforming gradient-based techniques into interpretable methods
Caroline Mazini Rodrigues, Nicolas Boutry, Laurent Najman
The explication of Convolutional Neural Networks (CNN) through xAI techniques often poses challenges in interpretation. The inherent complexity of input features, notably pixels ex…