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.
In: Proceedings of the 29th Annual International ACM SIGIR Confer- ence on Research and Development in Infor- mation Retrieval, pp
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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.