Información del curso

Course Contents
- Goals and challenges of explainability for computer vision
- Interpretability of classical machine learning models
- Global vs. local explanations
- Post hoc explanations
- Intrinsically explainable neural networks
- Evaluation of explanations
- Visualization techniques
- Applications of explanations 
- XAI beyond classification

Preconditions
Basic knowledge of computer vision, machine learning, and deep learning. For example, acquired through the courses Computer Vision I, Introduction to Artificial Intelligence, Deep Learning: Architectures & Methods, and/or Statistical Machine Learning.

Online Offerings
moodle