Publication | Closed Access
OCR-D
44
Citations
6
References
2019
Year
Unknown Venue
Deep Neural NetworksImage AnalysisMachine LearningData ScienceOcr SoftwarePattern RecognitionEngineeringText RecognitionText ProcessingOptical Character RecognitionComputer ScienceCharacter RecognitionDeep LearningDocument ProcessingHistorical Printed DocumentsSpeech Recognition
Various research projects were concerned with the development and adaptation of methods for OCR specifically for historical printed documents (cf. METAe [20], IMPACT [1], eMOP [9]). However, these initiatives have ended before the wide adoption of deep neural networks and, despite the various project's achievements, there remains a lack of OCR software that is a) comprehensive with regard to the challenges presented by the wide variety of historical documents and b) available as ready-to-use Free Software. The OCR-D project aims to rectify that.
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