PERO - Advanced content extraction and recognition for printed and handwritten documents for better accessibility and usability

Czech title:Pokročilá extrakce a rozpoznávání obsahu tištěných a rukou psaných digitalizátů pro zvýšení jejich přístupnosti a využitelnosti
Reseach leader:Smrž Pavel
Team leaders:Bařina David, Hradiš Michal, Juránek Roman, Zemčík Pavel
Team members:Beneš Karel, Kodym Oldřich
Agency:Ministry of Culture Czech Republic
Keywords:Optical character recognition, handwriting recognition, natural language processing, quality enhancement, language model, convolutional neural networks recurrent neural networks
The project aims to create technology and tools which would improve accessibility of digitized historic documents. These tools, based on state of the art methods from computer vision, machine learning and language modeling, will enable existing digital archives and libraries to provide full-text search and content extraction for low quality historic printed and all hand written documents - which can not be automatically processed by the currently available tools. The project extends automation and capabilities of digitization pipeline by providing tools for automated quality assessment and control, quality improvement, automated text transcription of historic printed documents, semi-automated hand written text transcription, and automatic extraction of semantic information from semi-structured documents (e.g. library catalogs and birth records). The created tools and techniques will be validated by processing selected collections of digitized materials and by a pilot operation by cooperation with Moravian Library.

Your IPv4 address:
Switch to IPv6 connection

DNSSEC [dnssec]