Outputs (18)

NAME – A Rich XML Format for Named Entity and Relation Tagging (2023)
Conference Proceeding
Clausner, C., Pletschacher, S., & Antonacopoulos, A. (2023). NAME – A Rich XML Format for Named Entity and Relation Tagging. In HIP '23: Proceedings of the 7th International Workshop on Historical Document Imaging and Processing (91-96). https://doi.org/10.1145/3604951.3605521

We present NAME XML, a schema for named entities and relations in documents. The standout features are: option to reference a variety of document formats (such as PAGE XML or plain text), support of entity hierarchies, custom entity types via ontolog... Read More about NAME – A Rich XML Format for Named Entity and Relation Tagging.

Flexible character accuracy measure for reading-order-independent evaluation (2020)
Journal Article
Clausner, C., Pletschacher, S., & Antonacopoulos, A. (2020). Flexible character accuracy measure for reading-order-independent evaluation. Pattern Recognition Letters, 131, 390-397. https://doi.org/10.1016/j.patrec.2020.02.003

The extraction of textual information from scanned document pages is a fundamental stage in any digitisation effort and directly determines the success of the overall document analysis and understanding application scenarios. To evaluate and improve... Read More about Flexible character accuracy measure for reading-order-independent evaluation.

A cloud-hosted MapReduce architecture for syntactic parsing (2019)
Conference Proceeding
Woldemariam, Y., Pletschacher, S., Clausner, C., & Bass, J. (2019). A cloud-hosted MapReduce architecture for syntactic parsing. In Kallithea, Greece. https://doi.org/10.1109/SEAA.2019.00024

Syntactic parsing is a time-consuming task innatural language processing particularlywherea largenumber of text files are beingprocessed. Parsingalgorithms are conventionally designed to operate on a single machine in a sequenti... Read More about A cloud-hosted MapReduce architecture for syntactic parsing.

Efficient and effective OCR engine training (2019)
Journal Article
Clausner, C., Antonacopoulos, A., & Pletschacher, S. (2020). Efficient and effective OCR engine training. International Journal on Document Analysis and Recognition, 23(1), 73-78. https://doi.org/10.1007/s10032-019-00347-8

We present an efficient and effective approach to train OCR engines using the Aletheia document analysis system. All components required for training are seamlessly integrated into Aletheia: training data preparation, the OCR engine’s training proces... Read More about Efficient and effective OCR engine training.

ICDAR2017 Competition on Recognition of Early Indian Printed Documents – REID2017 (2017)
Conference Proceeding
Clausner, C., Antonacopoulos, A., Derrick, T., & Pletschacher, S. (2017). ICDAR2017 Competition on Recognition of Early Indian Printed Documents – REID2017. . https://doi.org/10.1109/ICDAR.2017.230

This paper presents an objective comparative evaluation of page analysis and recognition methods for historical documents with text mainly in Bengali language and script. It describes the competition (modus operandi, dataset and evaluation methodolog... Read More about ICDAR2017 Competition on Recognition of Early Indian Printed Documents – REID2017.

ICDAR2017 Competition on Recognition of Documents with Complex Layouts – RDCL2017 (2017)
Conference Proceeding
Clausner, C., Antonacopoulos, A., & Pletschacher, S. (2017). ICDAR2017 Competition on Recognition of Documents with Complex Layouts – RDCL2017. . https://doi.org/10.1109/ICDAR.2017.229

This paper presents an objective comparative evaluation of page segmentation and region classification methods for documents with complex layouts. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context o... Read More about ICDAR2017 Competition on Recognition of Documents with Complex Layouts – RDCL2017.

Creating a complete workflow for digitising historical census documents : considerations and evaluation (2017)
Conference Proceeding
Clausner, C., Hayes, J., Antonacopoulos, A., & Pletschacher, S. (2017). Creating a complete workflow for digitising historical census documents : considerations and evaluation. . https://doi.org/10.1145/3151509.3151525

The 1961 Census of England and Wales was the first UK census to make use of computers. However, only bound volumes and microfilm copies of printouts remain, locking a wealth of information in a form that is practically unusable for research. In this... Read More about Creating a complete workflow for digitising historical census documents : considerations and evaluation.

Unearthing the recent past : digitising and understanding statistical information from census tables (2017)
Conference Proceeding
Clausner, C., Hayes, J., Antonacopoulos, A., & Pletschacher, S. (2017). Unearthing the recent past : digitising and understanding statistical information from census tables. In Proceedings of the 2nd International Conference on Digital Access to Textual Cultural Heritage - DATeCH2017. https://doi.org/10.1145/3078081.3078106

Censuses comprise a wealth of information at a large (national) scale that allow governments (who commission them) and the public to have a detailed snapshot of how people live (geographical distribution and characteristics). In addition to underpinn... Read More about Unearthing the recent past : digitising and understanding statistical information from census tables.

Effective geometric restoration of distorted historical documents for large-scale digitization (2017)
Journal Article
Yang, P., Antonacopoulos, A., Clausner, C., Pletschacher, S., & Qi, J. (2017). Effective geometric restoration of distorted historical documents for large-scale digitization. IET Image Processing, 11(10), 841-853. https://doi.org/10.1049/iet-ipr.2016.0973

Due to storage conditions and material’s non-planar shape, geometric distortion of the 2-D content is widely present in scanned document images. Effective geometric restoration of these distorted document images considerably increases character recog... Read More about Effective geometric restoration of distorted historical documents for large-scale digitization.

Quality prediction system for large-scale digitisation workflows (2016)
Conference Proceeding
Clausner, C., Pletschacher, S., & Antonacopoulos, A. (2016). Quality prediction system for large-scale digitisation workflows. . https://doi.org/10.1109/das.2016.82

The feasibility of large-scale OCR projects can so far only be assessed by running pilot studies on subsets of the target document collections and measuring the success of different workflows based on precise ground truth, which can be very costly to... Read More about Quality prediction system for large-scale digitisation workflows.