| 書目名稱 | Cursive Script Text Recognition in Natural Scene Images |
| 副標(biāo)題 | Arabic Text Complexi |
| 編輯 | Saad Bin Ahmed,Muhammad Imran Razzak,Rubiyah Yusof |
| 視頻video | http://file.papertrans.cn/242/241545/241545.mp4 |
| 概述 | Offers a broad and structured overview of state-of-the-art methods.Introduces and briefly describes the characteristics and complexities.Highlights the problems involved with Arabic scene text.Discuss |
| 圖書封面 |  |
| 描述 | This book offers a broad and structured overview of the state-of-the-art methods that could be applied for context-dependent languages like Arabic. It also provides guidelines on how to deal with Arabic scene data that appeared in an uncontrolled environment impacted by different font size, font styles, image resolution, and opacity of text..?.Being an intrinsic script, Arabic and Arabic-like languages attract attention from research community. There are a number of challenges associated with the detection and recognition of Arabic text from natural images. This book discusses these challenges and open problems and also provides insights into the complexities and issues that researchers encounter in the context of Arabic or Arabic-like text recognition in natural and document images. It sheds light on fundamental questions, such as a) How the complexity of Arabic as a cursive scripts can be demonstrated b) What the structure of Arabic text is and how to consider the features from a given text and c) What guidelines should be followed to address the context learning ability of classifiers existing in machine learning.. |
| 出版日期 | Book 2020 |
| 關(guān)鍵詞 | Cursive script; Deep learning; Arabic like; Classifiers; Context analysis; Sequential learning |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-15-1297-1 |
| isbn_softcover | 978-981-15-1299-5 |
| isbn_ebook | 978-981-15-1297-1 |
| copyright | Springer Nature Singapore Pte Ltd. 2020 |
|Archiver|手機(jī)版|小黑屋|
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