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Modeled Recognition and Extraction of Information from Chart Imageries Mishchenko1, Natalia Vassilieva2 CEA, Grenoble France 2 HP Labs St. Petersburg Russia ales.mishchenko×mail. Ru, nvassilieva×hp.com1ABSTRACT:

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What is model-based recognition and extraction?

Model-based recognition and extraction is a process that involves using predefined models to identify and extract specific information from data.

Who is required to file model-based recognition and extraction?

Entities or individuals who are dealing with large amounts of data and need to extract specific information from it are required to file model-based recognition and extraction.

How to fill out model-based recognition and extraction?

To fill out model-based recognition and extraction, one must first create or obtain the necessary models for the data being analyzed. Then, the models are applied to the data to extract the desired information.

What is the purpose of model-based recognition and extraction?

The purpose of model-based recognition and extraction is to automate the process of identifying and extracting specific information from data, making it more efficient and accurate.

What information must be reported on model-based recognition and extraction?

The specific information that must be reported on model-based recognition and extraction depends on the requirements of the project or analysis being conducted, but typically includes details on the models used, the data processed, and the extracted information.

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