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Department of Information Technology

Hand Written Text Recognition

This cross disciplinary initiative takes its point of departure in the analysis of handwritten text manuscripts using computational methods from image analysis and linguistics. It sets out to develop a manuscript analysis technology providing automatic tools for large-scale transcription, linguistic analysis, digital paleography and generic data mining of historical manuscripts. Our mission is to develop technology that will push the digital horizon back in time, by enabling digital analysis of handwritten historical materials for both researchers and the public.

Research Interests

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Contact People

Anders Hast
Professor
Carl Nettelblad
Associate Professor, Technical Coordinator

Main research in methods for QTL analysis, haplotype reconstruction, and methods for single particle X-ray diffractive imaging.

Ekta Vats
Researcher
Raphaela Heil
PhD Student

More Information

For more information please visit q2b!

Updated  2019-11-19 10:13:14 by Elisabeth Wetzer.