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This paper explores the use of machine vision algorithms to retrieve visual patterns in paintings, addressing the challenges faced by art historians in identifying genealogical links between artworks. The authors developed a methodology and tool for annotating clusters of similar paintings, demonstrating that fine-tuning pre-trained convolutional neural networks significantly enhances retrieval performance compared to traditional methods. The study also emphasizes the importance of digitized art collections
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- Cop copscholarship
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- EN