An Artificial Intelligence System for Automatic Recognition of Punches in Fourteenth-Century Panel Painting
نویسندگان
چکیده
In Late-Medieval panel paintings from the Tuscan area, mechanical tools called punches were used to impress repeated motifs on gold foils create decorative patterns. Such patterns can be as clues objectively support attribution of paintings, proposed by art historian Erling S. Skaug in his decades-long study punches. We investigate feasibility employing automatic pattern recognition techniques for accelerating process classification experts working field. propose a system composed (a) Convolutional Neural Network categorizing punch contained frame, and (b) an additional component uncertainty estimation, aimed at recognizing possible Out-of-Distribution (OOD) samples. After collecting set 14th century Tuscany, we train which achieves very high test-set accuracy. As far estimation is concerned, experiment with two techniques, OpenGAN II-loss, both exhibiting positive results. The former seems work better specific data extracted images while latter showcases more consistent behavior when considering OOD obtained randomly. These outcomes indicate that application our feasible, although subsequently show experiments larger datasets might required.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3236502