2 papers
cs.AI2025
Concept-Based Explainable Artificial Intelligence: Metrics and Benchmarks
Halil Ibrahim Aysel, Xiaohao Cai, Adam Prugel-Bennett
Concept-based explanation methods, such as concept bottleneck models (CBMs), aim to improve the interpretability of machine learning models by linking their decisions to human-unde…
cs.CV2024
Semantic Segmentation by Semantic Proportions
Halil Ibrahim Aysel, Xiaohao Cai, Adam Prügel-Bennett
Semantic segmentation is a critical task in computer vision aiming to identify and classify individual pixels in an image, with numerous applications in for example autonomous driv…