What it is
We present an AI-driven explainable approach to assist painting attribution with up to 97.9% recall, 95.8% accuracy when highly confident, and methods that identify the most relevant areas. This work supports human–AI collaboration by incorporating expert guidance, expanding the outputs with explainable visualizations, tailoring settings to users’ needs, thorough calibrations to avoid…
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Filed underExplainable Artificial Intelligence (XAI), Cultural Heritage Materials Analysis, Image Processing and 3D Reconstruction