In this three year project, funded by Riksbankens Jubileumsfond (RJ) and based at the Swedish Labour Movement’s Archives and Library, I have been focusing on Handwritten Text Recognition (HTR) of the notes.

Paper

  • Exploring Handwritten Document Collections: An EPSC-Based Approach for Feature Extraction and Similarity Analysis.
    Anders Hast, Örjan Simonsson.
    In the Proceedings of the 21st Conference on Information and Research science Connecting to Digital and Library science. Udine, Italy, February 20-21, 2025. pp. 1-8. pdf.


Master Thesis Projects

Writer Adaptive Hand-Written Text Recognition With Confidence-Based Ensemble: Developing and implementing a pipeline to transcribe Swedish documents – Developing and implementing a pipeline to transcribe Swedish documents.
Zhihao Yang. 2024.

Handwritten Text Recognition Using a Vision Transformer.
Kurén Jonathan, Sundberg Martin. 2023.

Recognition of Handwritten Swedish Sentences With Deep Learning.
Hussain Kara Fallah. 2023.

Semi-automatic Segmentation & Alignment of Handwritten Historical Text Images with the use of Bayesian Optimisation.
Philip MacCormack. 2023.

Independent Projects 15hp

Histogram of Oriented Gradients in a Vision Transformer.
Heja Cengiz, David Lood, Jakob Malmsten. 2022.


Course Project Supervision

Transfer Learning for Handwritten Text Recognition of Old Swedish Text 
Zhihao Yang, Vijayaadhithan Tamilselvan, Sarath Peringayi Suresh. 2023

Classification of handwritten words.
Hussain Kara Fallah. 2022.

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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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