Pilot experiment DSS Hasmo/Herod fraglet-based dataset bipartitioning (80x80 Kohonen map)

As a pilot experiment for manuscript dating in the DSS/IAA ERC project, 590 scans, each labeled on global style (Hasmonean/Herodian) were binarized using Maruf Dhali's BiNet neural network. Fragmented connected component contours were computed and compared to a precomputed 80x80 Kohonen map of DSS fragmented connected-component contours (*.fco3). Kohonen cells obtained the frequency counts for the labels Hasmonean and Herodian. Individual scans were characterized by their total Hasmo, Herod counts. Augmentation using random elastic morphing was used to obtain a comparable number of FCO3s per scan. The 2D feature vector with total counts #Hasmo and #Herod was subjected to PCA, with the goal of identifying the most informative axis for the Hasmonean/Herodian distinction. 93% of the samples (scans) could be correctly classified. Although this is a simple, within dataset bipartitioning experiment, the good results were taken as an indicator that the FCO3 fraglet feature would be useful in a more fine-grained style-based manuscript dating attempt using the radiocarbon-labeled data.