How do I evaluate change detection models?

How do I evaluate change detection models?

To evaluate change detection models, you can use metrics like precision, recall, F1-score, and IoU (Intersection over Union).

What datasets are commonly used for this evaluation?

Common datasets include the Change Detection 2014 dataset, the LEVIR dataset, and the WHU dataset.

Can you explain precision and recall in this context?

Sure! Precision measures the accuracy of the detected changes, while recall measures the model's ability to identify all actual changes.

What are some challenges in evaluating these models?

Challenges include dealing with noise in data, varying scales of changes, and the subjective nature of what constitutes a 'change'.