In this three-year project (2020–2022), the focus was on automatic handwritten text transcription, and strike through removal, of the short hand (stenography) of the famous Swedish children author Astrid Lindgren. It resulted in one PhD thesis, five papers and two master thesis project. I was acting as supervisor for, but not co-author of two papers.

Phd Thesis

Heil, Raphaela. Document Image Processing for Handwritten Text Recognition: Deep Learning-based Transliteration of Astrid Lindgren’s Stenographic Manuscripts. pdf

Papers

A Study of Augmentation Methods for Handwritten Stenography Recognition.
Heil Raphaela, Breznik Eva.
IbPRIA 2023: 11th Iberian Conference on Pattern Recognition and Image Analysis.
2023.

Handwritten Stenography Recognition and the LION Dataset.
Heil Raphaela, Nauwerck Malin.
Submitted, 2023.

Magnitude of Semicircle Tiles in Fourier-space – A Handcrafted Feature Descriptor for Word Recognition using Embedded Prototype Subspace Classifiers.
A. Hast.
Journal of WSCG, ISSN 1213-6972, Vol.30. No.1-2, DOI: 10.24132/JWSCG.2022.10, Journal, pp. 82-90. 2022, pdf

Shorthand Secrets: Deciphering Astrid Lindgren’s Stenographed Drafts with HTR Methods.
Heil Raphaela, Nauwerck Malin, Hast Anders.
Italian Research Conference on Digital Libraries IRCDL 2021.
2021. p. 169-177.

Paired Image to Image Translation for Strikethrough Removal from Handwritten Words.
Heil Raphaela, Vats Ekta, Hast Anders.
15th IAPR International Workshop on Document Analysis Systems (DAS), MAY 22-25, 2022, La Rochelle Univ, La Rochelle, FRANCE.
Springer Nature, 2022. Vol. 13237, p. 309-322.

Strikethrough Removal from Handwritten Words Using CycleGANs.
Heil Raphaela, Vats Ekta, Hast Anders.
International Conference on Document Analysis and Recognition (ICDAR).
Springer, 2021. Vol. 12824, p. 572-586.

“The Stenographic Code”, M. Nauwerck, A. Hast. Children’s Literature and Digital Humanities, University of Antwerp, Thursday 22 and Friday 23 October 2020.

Master Thesis

Towards word alignment and dataset creation for shorthand documents and transcripts.
Ryan Elisabeth.
Supervisor: Anders Hast, 2021.

Towards a Language Model for Stenography: A Proof of Concept.
Langstraat, Naomi Johanna.
Supervisor: Nivre Joakim. 2022.


Published by Anders

Anders Hast received a PhD in Computerised Image processing at Uppsala university in 2004. In 2011 he spent one year at IIT, CNR, Pisa in Italy as an ERCIM fellow and after that he received a full time position as associate professor and in 2019 he became professor in image processing, both at Uppsala University. He has been affiliated with UPPMAX super computer centre where he worked as an application expert in Scientific Visualisation and later in the field of digital humanities together with the Centre for digital humanities in Uppsala. His recent research has focused on image processing and computer vision, for applications in microscopy, aerial photography, object recognition and especially hand written text recognition and face recognition.

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