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Form Analysis by Neural Classification of Cells
Abstract : Our aim in this paper is to present a methodology for linearly combining multi neural classifier for cell analysis of forms. Features used for the classification are relative to the text orientation and to its character morphology. Eight classes are extracted among numeric, alphabetic, vertical, horizontal, capitals, etc. Classifiers are multi-layered perceptrons considering firstly global features and refining the classification at each step by looking for more precise features. The recognition rate of the classifiers for 3. 500 cells issued from 19 forms is about 91 %.
Cited literature [3 references]
https://hal.inria.fr/inria-00133716
Contributor : Yolande Belaid Connect in order to contact the contributor
Submitted on : Tuesday, February 27, 2007 - 3:06:16 PM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM
Contributor : Yolande Belaid Connect in order to contact the contributor
Submitted on : Tuesday, February 27, 2007 - 3:06:16 PM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM
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