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Found 3 papers, 1 papers with code
Thread Counting in Plain Weave for Old Paintings Using Semi-Supervised Regression Deep Learning Models
Previous approaches were based on Fourier analysis, which is quite robust for some scenarios but fails in some others, in machine learning tools, that involve pre-labeling of the painting at hand, or the segmentation of thread crossing points, that provides good estimations in all scenarios with no need of pre-labeling.
On the Power Spectral Density Applied to the Analysis of Old Canvases
We apply these results to several masterpieces of the 17th and 18th centuries from the Museo Nacional del Prado to show that this approach yields accurate results in thread counting and is very useful for paintings comparison, even in situations where previous methods fail.
Complex-Valued Gaussian Processes for Regression
In the experiments included, we show how CGPR successfully solve systems where real and imaginary parts are correlated.
