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Simultaneous Detection And Recognition of Named En

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911QX-10-C-0023
Agency Tracking Number: A092-042-1357
Amount: $119,083.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A09-042
Solicitation Number: 2009.2
Solicitation Year: 2009
Award Year: 2009
Award Start Date (Proposal Award Date): 2009-11-25
Award End Date (Contract End Date): 2010-06-02
Small Business Information
1427 Cerro Verde
San Jose, CA 94043
United States
DUNS: 115713492
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Ismail Haritaoglu
 (650) 793-9453
Business Contact
 Esin Darici Haritaoglu
Title: VP
Phone: (650) 646-5799
Research Institution

Polar Rain proposes to study, and investigate approaches to develop a new data and computational models combining image-based features with language model to extract name entities in degraded Arabic printed and handwritten documents. The proposed approach will use robust shape features and computational model that simultaneously clean and restore document images and detect named entities. The proposed data models are specifically designed taking named entities characteristics into consideration. In phase-I, we will investigate how to design such data model which contains both image and language features together for complex degraded document images. Our computational models will use generative and descriptive models to extract names from recognition results that may contain significant error or partial recognition. The proposed approach will work both in handwritten and printed Arabic scripts. We will design a flexible software architecture so that the solution can be extended to other similar languages, such as Pashto, without extensive work and allows 3rd party OCR to be integrated with the system. We will evaluate and conduct experiments to measure feasibility and superiority of proposed solution over exiting NEE solution.

* Information listed above is at the time of submission. *

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