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arXiv 2206.04575cs.CVcs.AIcs.IRcs.LG
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Transformer based Urdu Handwritten Text Optical Character Reader

FAST NUCES(巴基斯坦国立计算机与新兴科学大学)

Mohammad Daniyal Shaiq, Musa Dildar Ahmed Cheema, Ali Kamal

英文摘要:

Extracting Handwritten text is one of the most important components of digitizing information and making it available for large scale setting. Handwriting Optical Character Reader (OCR) is a research problem in computer vision and natural language processing computing, and a lot of work has been done for English, but unfortunately, very little work has been done for low resourced languages such as Urdu. Urdu language script is very difficult because of its cursive nature and change of shape of characters based on it's relative position, therefore, a need arises to propose a model which can understand complex features and generalize it for every kind of handwriting style. In this work, we propose a transformer based Urdu Handwritten text extraction model. As transformers have been very successful in Natural Language Understanding task, we explore them further to understand complex Urdu Handwriting.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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