TEXPROS: AN INTELLIGENT DOCUMENT PROCESSING SYSTEM

1994 ◽  
pp. 103-135
Author(s):  
JASON T. L. WANG ◽  
PETER A. NG
Keyword(s):  
Processing System ◽  
Document Processing

Implementation for Personal Document Processing System

2017 ◽  
Author(s):  
Ahmad Q. Alhamad ◽  
Ahmed M. Elshamy ◽  
Waleed Maqableh ◽  
Asma Qasim
Keyword(s):  
Processing System ◽  
Document Processing

Hardware design of a letter-driven OCR and document processing system

1996 ◽  
Vol 19 (3) ◽  
pp. 275-294 ◽  
Author(s):  
N. Bourbakis ◽  
N. Pereira ◽  
S. Mertoguno
Keyword(s):  
Hardware Design ◽  
Processing System ◽  
Document Processing

MANICURE document processing system

1998 ◽  
Author(s):  
Kazem Taghva ◽  
Allen Condit ◽  
Julie Borsack ◽  
John Kilburg ◽  
Changshi Wu ◽  
...  
Keyword(s):  
Processing System ◽  
Document Processing

TEXPROS: AN INTELLIGENT DOCUMENT PROCESSING SYSTEM

1992 ◽  
Vol 02 (02) ◽  
pp. 171-196 ◽  
Author(s):  
JASON T. L. WANG ◽  
PETER A. NG
Keyword(s):  
Data Model ◽  
Process Model ◽  
Processing System ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Document Processing ◽  
Retrieval Systems ◽  
File Structure ◽  
Processing Techniques ◽  
Specification Techniques

This paper presents the design of an intelligent document processing system, called TEXPROS. The system is a combination of filing and retrieval systems, which supports storing, extracting, classifying, categorizing, retrieving and browsing information from a variety of documents. TEXPROS is built based on object-oriented programming and rule-based specification techniques. In this paper, we describe main design goals of the system, its data model, logical file structure, and strategies for document classification and categorization. We also illustrate various retrieval methods and query processing techniques through examples. Finally applications of TEXPROS are presented, where we suggest ways in which the use of the system may alter the software process model.

An automatic document processing system for medical data extraction

Measurement ◽  
2015 ◽  
Vol 61 ◽  
pp. 88-99 ◽  
Author(s):  
Francesco Adamo ◽  
Filippo Attivissimo ◽  
Attilio Di Nisio ◽  
Maurizio Spadavecchia
Keyword(s):  
Data Extraction ◽  
Processing System ◽  
Medical Data ◽  
Document Processing

scholarly journals Indian Handwritten Script Identification System based on Random Forest Tree Ensembles

2019 ◽  
Vol 8 (2) ◽  
pp. 2097-2103
Keyword(s):  
Random Forest ◽  
Processing System ◽  
Forest Tree ◽  
Structural Features ◽  
Identification System ◽  
Document Processing ◽  
Script Language ◽  
Handwritten Documents ◽  
Script Identification ◽  
Random Forest Tree

The work proposal addresses to introduce a methodology for Indian unconstrained handwritten script identification by practicing distinct features and classifiers. By utilizing classifiers like RF, SVM, k-NN, and LDA for Indian script identification using statistical, geometric, and structural features. To preserve all the information present on handwritten documents such as historical, medieval, inscription, financial administration, public records, government archives, letters, land councils, various agreements, etc. in digitalize form needs textual document processing system (e.g. OCR). To build a precise and productive multi-script/language textual document processing system must have script identification. For this study use, total 1288 (line wise) samples of ten scripts use in India are collected from different persons of different gender, age, education and region (rural or urban). After successful training and testing, 81.8% and 0.252 accuracies and the OOB error rate are achieved by Random Forest respectively. And 77.8%, 73.5%, and 65.5% accuracy is achieved in SVM, k-NN and LDA classifiers respectively

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