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Data-driven Automatic Attribution of Azerbaijani Flat Woven Carpets.

Bakirov, R., Taghieva, R., Eyvazli, N. and Mammadzada, U., 2022. Data-driven Automatic Attribution of Azerbaijani Flat Woven Carpets. In: SUMAC '22: Proceedings of the 4th ACM International Workshop on Structuring and Understanding of Multimedia HeritAge Contents, 10 October 2022, Lisboa, Portugal, 15-21.

Full text available as:

Automatic_carpet_attribution_final.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.


DOI: 10.1145/3552464.3555682


Carpet attribution is an important task for studying the carpets and textiles, and more generally the history and culture of the communities producing these carpets. However, this is not an easy task, often relying on experts' subjective opinion or complex chemical or radiographical analysis, often not available to many practitioners. In this work, building on the success of applying machine learning and artificial intelligence methods in different fields, we present another, data-driven approach for carpet attribution. Based on a large dataset of Azerbaijani flat woven carpets we have developed a novel machine learning based data-driven carpet attribution system, which successfully determines their types, schools and weaving century, achieving up to 98% accuracy of the attribution.

Item Type:Conference or Workshop Item (Paper)
Additional Information:MM '22: The 30th ACM International Conference on Multimedia Lisboa Portugal 10 October 2022
Group:Faculty of Science & Technology
ID Code:37814
Deposited By: Symplectic RT2
Deposited On:25 Nov 2022 12:16
Last Modified:25 Nov 2022 12:16


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