OCCAM (OCR, ClassificAtion & Machine Translation) responds to action line "Integration projects" on the integration (and extension) of CEF (Connecting Europe Facility) Automated Translation into multilingual digital cross-border services. The Action proposes the integration of image classification, Translation Memories (TMs), Optical Character Recognition (OCR), and Machine Translation (MT) to support the automated translation of scanned documents - a document type that currently cannot be processed by the CEF eTranslation service.
OCCAM will develop two use cases: (i) the Business Registers Interconnection System (BRIS) use case and (ii) the Digital Humanities use case.

Description in Czech
OCCAM (OCR, ClassificAtion & Machine Translation) responds to action line "Integration projects" on the integration (and extension) of CEF (Connecting Europe Facility) Automated Translation into multilingual digital cross-border services. The Action proposes the integration of image classification, Translation Memories (TMs), Optical Character Recognition (OCR), and Machine Translation (MT) to support the automated translation of scanned documents - a document type that currently cannot be processed by the CEF eTranslation service.
OCCAM will develop two use cases: (i) the Business Registers Interconnection System (BRIS) use case and (ii) the Digital Humanities use case.

Keywords
OCR, Classification, Machine Translation

Key words in Czech
OCR, Classification, Machine Translation

INEA/CEF/ICT/A2018/1741945

English

Smrž Pavel, doc. RNDr., Ph.D. - principal person responsible
Homoliak Ivan, doc. Ing., Ph.D. - fellow researcher
Michal Bohumil, Ing. - fellow researcher
Mrazíková Libuše, Mgr. - fellow researcher
Musil Petr, Ing., Ph.D. - fellow researcher
Najman Pavel, Ing. - fellow researcher
Otáhalová Sylva - fellow researcher
Pirová Zuzana, Ing. - fellow researcher

Department of Computer Graphics and Multimedia
- responsible department (28.8.2018 - not assigned)
CrossLang
- co-beneficiary (1.10.2019 - 30.9.2021)
Department of Computer Graphics and Multimedia
- beneficiary (1.10.2019 - 30.9.2021)

KIŠŠ, M.; BENEŠ, K.; HRADIŠ, M. AT-ST: Self-Training Adaptation Strategy for OCR in Domains with Limited Transcriptions. In Lladós J., Lopresti D., Uchida S. (eds) Document Analysis and Recognition - ICDAR 2021. Lecture Notes in Computer Science. Lausanne: Springer Nature Switzerland AG, 2021. p. 463-477. ISBN: 978-3-030-86336-4.
Detail

Responsibility: Smrž Pavel, doc. RNDr., Ph.D.