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31#
發(fā)表于 2025-3-26 21:52:40 | 只看該作者
32#
發(fā)表于 2025-3-27 03:21:20 | 只看該作者
33#
發(fā)表于 2025-3-27 08:08:09 | 只看該作者
34#
發(fā)表于 2025-3-27 12:32:32 | 只看該作者
35#
發(fā)表于 2025-3-27 15:36:54 | 只看該作者
Building Data Sets for Indian Language OCR Researchges. In this chapter, we present our activities in this direction. Our corpus consists of more than 600000 document images in Indian scripts. A parallel text is aligned to the images to obtain word- and symbol-level annotated data sets. We describe the process we follow and the status of the activit
36#
發(fā)表于 2025-3-27 19:55:42 | 只看該作者
On OCR of Major Indian Scripts: Bangla and Devanagaring structural similarities, these two scripts can be tackled under a single framework. The proposed approach starts with character and symbol segmentation and employs three recognizers for symbols of different zones. For the middle zone, a two-stage approach with group and individual symbol recogniz
37#
發(fā)表于 2025-3-27 22:30:20 | 只看該作者
A Complete Machine-Printed Gurmukhi OCR Systemis still in its infancy. Complete OCR systems have recently been developed for Devanagari and Bangla scripts. However, research in the field of recognition of Gurmukhi script faces major problems mainly due to the unique characteristics of the script such as connectivity of characters on a headline,
38#
發(fā)表于 2025-3-28 05:08:33 | 只看該作者
39#
發(fā)表于 2025-3-28 10:10:36 | 只看該作者
Design of a Bilingual Kannada–English OCRr presents an approach towards designing a bilingual OCR that can process documents containing both English and Kannada scripts which are used by the Kannada language of the southern Indian state of Karnataka. We report an efficient script identification scheme for discriminating Kannada from Roman
40#
發(fā)表于 2025-3-28 13:17:27 | 只看該作者
Recognition of Malayalam Documentsthis language will be of immense help in a spectrum of applications ranging from data entry to reading aids. The Malayalam script has a large number of similar characters making the recognition problem challenging. In this chapter, we present our approach for recognition of Malayalam documents, both
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