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Applied Machine Learning for Historical Document Image Analysis

ABG-100591 Thesis topic
2021-10-14 Other public funding
Østfold University College
Halden (and Fredrikstad) - Norway
Applied Machine Learning for Historical Document Image Analysis
  • Computer science

Topic description

The overall aim of the HUGIN-MUNIN project is to develop technological solutions that will enable the use of Handwritten Text Recognition (HTR) without the requirements for massive manual annotation and model training. The solutions developed will go beyond traditional supervised  machine learning by using ideas from active learning, unsupervised learning, transfer learning, and zero-shot learning. It will also leverage natural language processing resources recently developed for the Norwegian language.

The project will significantly increase the scope and variety of sources available for data-driven research on Norwegian culture and society. It will also democratize the access to knowledge by enabling the public to read documents that have so far been mainly reserved for domain experts and scholars. The Ph.D student is expected to collaborate with other consortium members in the project which includes National Library of Norway (the digitization hub for the entire country), along with Lumex AS from Norway and another technology partner Teklia from France both internationally recognized organizations on developing handwritten text recognition systems.

Within the project, the PhD candidate will work mainly in the following areas:

Zero-shot word recognition and spotting (out-of-lexicon word spotting) by proposing novel methods pertinent to Norwegian handwritten texts. To develop GAN-based methods to emulate handwritten text on the basis of specific writer styles and also generic handwriting styles representing a specific time period. These could be used to synthetically generate  texts for training purposes and  to Fine-tune the base GAN model on specific handwriting.

The successful candidate will be a member of an active research group at Østfold University College. The candidate is expected to do research, develop prototype implementations and write research papers on the topic of the project. Research visits to different relevant research groups in European countries will also be possible on availability of funds and opportunity.

Funding category

Other public funding

Funding further details

Presentation of host institution and host laboratory

Østfold University College

Østfold University College is a state college with around 7,800 students and 620 employees. The university college is located in Fredrikstad and Halden and has a broad study portfolio ranging from professional studies programmes to arts programmes, both at bachelor's and master's level.

The university college is growing and has an ambitious strategy for the future, including establishing an interdisciplinary doctoral programme "Digitalisation and Society", delivering outstanding socially relevant educations, and strengthening interaction with business and social life – both in education and research.

The core of the college's activities is to provide students with access to outstanding socially relevant and profession-oriented studies. We will ensure that students have a great learning outcome and are ready for a working life with rapid restructuring, by focusing on quality, on technology, on infrastructure and on new teaching methods. The students will also experience a close relationship between theoretical knowledge, fields of profession and societal needs, and the college will therefore strengthen its strategic and binding cooperation with working life.

Although we have a strong regional foundation, our education programmes are increasingly characterized by an international commitment. Østfold University College also works to strengthen its partnerships with selected national and international educational institutions.


We are looking for applicants who are passionate about developing Østfold University College and want to build an attractive, competent and development-oriented college.

Candidate's profile

Essential Criteria

- completed a Master’s degree or equivalent within the field of Computer/Electronics/Electrical Engineering, Computer Science, Computer Applications, Mathematics, Statistics or a closely related field.

- the average grade point of courses should be B (for candidates with publications in reputed venues or with prior work experience, this might be relaxed). 

- hands-on experience with Popular Deep-learning Libraries/ Environments like Keras, Tensorflow, Pytorch.

- fluent oral and written communication skills in English 

Desired Criteria: 

- knowledge in Machine Learning, Computer Vision, Image Analysis

- sound knowledge of advanced multi-variable Calculus, Linear Algebra, Statistics

- very good programming skills in C/C++/Python

- prior publications in top tier Journals /conferences on Machine Learning, Computer Vision in general (even better if precisely in Document Image Analysis) 

- knowledge of Shell scripting 

Personal characteristics

- interpersonal skills and a willingness to work as part of an international team based in Norway

- organized and Self-motivated individual, eager to work with industry partners and colleagues on research problems

Emphasis will be placed on the following:

- prior academic and/or research performance

- prior relevant work experience (if applicable)

- the applicant’s own ideas of research themes and research design that would be relevant for the project proposal.

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