A deep learning perspective on Rubens' attribution

• URL: http://arxiv.org/abs/2511.22667v1
• Date: Thu, 27 Nov 2025 18:01:24 GMT
• Title: A deep learning perspective on Rubens' attribution
• Abstract summary: A convolutional neural network was trained on a dataset of verified and comparative artworks to identify micro-level stylistic features characteristic of the master s hand.<n>The model achieved high classification accuracy and demonstrated the potential of computational analysis to complement traditional art historical expertise.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This study explores the use of deep learning for the authentication and attribution of paintings, focusing on the complex case of Peter Paul Rubens and his workshop. A convolutional neural network was trained on a curated dataset of verified and comparative artworks to identify micro-level stylistic features characteristic of the master s hand. The model achieved high classification accuracy and demonstrated the potential of computational analysis to complement traditional art historical expertise, offering new insights into authorship and workshop collaboration.

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