xrt11/XAI-CODE
XAI-Explaining AI black box models
This project helps medical imaging specialists and researchers understand why an AI model classifies images the way it does, especially in fields like radiology. It takes your existing image classification model and input images, and generates explanations, such as saliency maps, that pinpoint which visual features contribute to a specific classification. This allows you to gain insights into the AI's decision-making process for image analysis.
No commits in the last 6 months.
Use this if you need to explain the reasoning behind an AI's image classification decisions, particularly in medical or scientific imaging.
Not ideal if your primary goal is to train a new image classifier from scratch or if you need explanations for non-image data.
Stars
8
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Language
Python
License
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Last pushed
Dec 26, 2024
Commits (30d)
0
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