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灰姑娘

Hans-Bernd Kittlaus,Samuel A. Frickerges. 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

時(shí)代

The Elements of Software Pricing,ng 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

Prognosis

遣返回國

Software Project Effort Estimationective it needs a different treatment due to some of its peculiarities. Research on Gujarati OCR is a recent development as compared to OCR research on many other Indic scripts. Here, in this chapter we present a detailed account of the state of the art of Gujarati document analysis and character re

Inculcate

https://doi.org/10.1007/978-1-4842-5025-9r 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