q2b-white

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.

  • Since January 2017 I take part in the following project within q2b: 2016 – 2021: Riksbankens Jubileumsfond, Jubileumsutlysningen Nya utsikter för humaniora och samhällsvetenskap, 13.4 MSEK. New Eyes on Sweden s Medieval Scribes. Scribal Attribution using Digital Palaeography in the Medieval Gothic Script. (Dnr NHS14-2068:1, PI Lasse Mårtensson).

My Group

  • Ekta Vats, Postdoc, funded by eSSENCE for two years. Starting date May 2, 2017. Title: Automatic hand written text recognition.
  • Raphaela Heil, Faculty funded PhD Student. Start date: January 15, 2018. Preliminary title: Computerized Image Processing in handwritten text Recognition.

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