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ArabiCCR: A commercial Arabic ruling court cases dataset with judicial decisions. [PDF]
Data BriefAlharbi T +3 more
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2013 IEEE Seventh International Conference on Semantic Computing, 2013
Recently, a large number of dataset repositories, catalogs and portals are emerging in the science and government realms. Once a large number of datasets are published on such data portals, the question arises how to retrieve datasets satisfying an information need. In this paper, we present an approach for retrieving datasets according to user queries.
Sven R. Kunze, Sören Auer
openaire +1 more source
Recently, a large number of dataset repositories, catalogs and portals are emerging in the science and government realms. Once a large number of datasets are published on such data portals, the question arises how to retrieve datasets satisfying an information need. In this paper, we present an approach for retrieving datasets according to user queries.
Sven R. Kunze, Sören Auer
openaire +1 more source
2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2020
Benchmark datasets are important in document image processing field, as they allow to analyze different approaches and compare their performances in a fair manner. There exist benchmark datasets for several alphabets such as Latin, Arabic and Chinese, but not the Hebrew alphabet. In this paper, a handwritten Hebrew dataset, HHD, is introduced.
Irina Rabaev +3 more
openaire +1 more source
Benchmark datasets are important in document image processing field, as they allow to analyze different approaches and compare their performances in a fair manner. There exist benchmark datasets for several alphabets such as Latin, Arabic and Chinese, but not the Hebrew alphabet. In this paper, a handwritten Hebrew dataset, HHD, is introduced.
Irina Rabaev +3 more
openaire +1 more source
2019 International Conference on Document Analysis and Recognition (ICDAR), 2019
In historical document image processing, datasets account for a significant part of any research, and are crucial for the diversity and abundance of experimental results, which contribute to the development of new algorithms to meet the new challenge. Moreover, they are very important for benchmarking processing algorithms.
Berat Kurar Barakat +2 more
openaire +1 more source
In historical document image processing, datasets account for a significant part of any research, and are crucial for the diversity and abundance of experimental results, which contribute to the development of new algorithms to meet the new challenge. Moreover, they are very important for benchmarking processing algorithms.
Berat Kurar Barakat +2 more
openaire +1 more source