Fine-tuned RegNetY-16GF reaches 99.16% accuracy classifying 48k century-old Czech archival pages into 11 visual content types, beating a 75% hand-crafted feature baseline, with models and data released publicly.
International Jour- nal on Document Analysis and Recognition (IJDAR)25(4), 305–338 (2022) https://doi
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Page image classifier fine-tuned on century-spanning archives of scanned documents for further content-specific processing
Fine-tuned RegNetY-16GF reaches 99.16% accuracy classifying 48k century-old Czech archival pages into 11 visual content types, beating a 75% hand-crafted feature baseline, with models and data released publicly.