abonte/protopdebug

Implementation of Concept-level Debugging of Part-Prototype Networks

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Experimental

This tool helps researchers in fields like medical imaging or biology understand why an AI model makes certain predictions, especially when dealing with image classification. You provide the AI model's training data and the model itself, and it helps you pinpoint specific visual 'concepts' or patterns that the AI is using to decide, for example, if an X-ray shows a disease or if a bird belongs to a certain species. This allows domain experts to identify if the AI is relying on misleading clues or irrelevant features.

No commits in the last 6 months.

Use this if you need to debug or gain confidence in an image classification AI model's decision-making process by understanding the visual features it considers important.

Not ideal if you are not working with image-based AI models, or if you only need to know how well a model performs without needing to understand its internal reasoning.

medical-imaging diagnostic-AI image-classification AI-explainability computational-biology
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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12

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Language

Python

License

MIT

Last pushed

May 09, 2023

Commits (30d)

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