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A Convolutional Neural Network as a Proxy for the XRF Approximation of the Chemical Composition of Archaeological Artefacts in the Presence of Inter-microscope Variability.

, , , , , and . IWANN (2), volume 12862 of Lecture Notes in Computer Science, page 260-271. Springer, (2021)

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A Convolutional Neural Network as a Proxy for the XRF Approximation of the Chemical Composition of Archaeological Artefacts in the Presence of Inter-microscope Variability., , , , , and . IWANN (2), volume 12862 of Lecture Notes in Computer Science, page 260-271. Springer, (2021)Deep learning for a swift non-invasive recognition and delineation of corrosive iron compounds present on the surface of unrestored archaeological artefacts., , , , , , and . KES, volume 207 of Procedia Computer Science, page 1303-1311. Elsevier, (2022)Study on Semantic Inpainting Deep Learning Models for Artefacts with Traditional Motifs., , , , and . IWANN (2), volume 14135 of Lecture Notes in Computer Science, page 479-490. Springer, (2023)A Deep Learning-based Surrogate for the XRF Approximation of Elemental Composition within Archaeological Artefacts before Restoration., , , , , and . KES, volume 192 of Procedia Computer Science, page 2002-2011. Elsevier, (2021)Semantic Segmentation for Corrosion Detection in Archaeological Artefacts before Restoration., , , , , and . SYNASC, page 246-251. IEEE, (2021)On Using Perceptual Loss within the U-Net Architecture for the Semantic Inpainting of Textile Artefacts with Traditional Motifs., , , , , , , and . SYNASC, page 276-283. IEEE, (2022)