Handwritten Phoenician Character Recognition and its Use to Improve Recognition of Handwritten Alphabets with Lack of Annotated Data

Lamyaa Sadouk
<span title="2020-02-15">2020</span> <i title="The World Academy of Research in Science and Engineering"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/naqzxq5hurh2bp2pnvwitnnx44" style="color: black;">International Journal of Advanced Trends in Computer Science and Engineering</a> </i> &nbsp;
Unlike Latin, the recognition of Phoenician handwritten characters remains at the level of research and experimentation. In fact, such recognition can contribute to performing tasks such as automatic processing of Phoenician administrative records and scripts, the digitization and the safeguarding of the written Phoenician cultural heritage. As such, the availability of a reference database for Phoenician handwritten characters is crucial to carry out these tasks. To this matter, a database for
more &raquo; ... Phoenician handwritten characters (PHCDB) is introduced for the first time in this paper. We also explore the challenges in the recognition of Phoenician handwritten characters by proposing a deep learning architecture trained on our database. Furthermore, we propose a transfer learning system based on Phoenician character shapes to improve the recognition performance of Tifinagh Handwritten character, and we thereby affirm the possibility of the Tifinagh alphabet being derived from the Phoenician alphabet. Finally, based on Phoenician characters, we introduce a fast, global and light-weight transfer learning system for the recognition of any alphabet which lacks annotated data.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.30534/ijatcse/2020/26912020">doi:10.30534/ijatcse/2020/26912020</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ysghomrbn5hppnau2vou4n4bgy">fatcat:ysghomrbn5hppnau2vou4n4bgy</a> </span>
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