scholarly journals Development of the documents comparison module for an electronic document management system

2019 ◽  
pp. 527-533
Author(s):  
M A Mikheev ◽  
P Y Yakimov
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Document Management ◽  
Electronic Document ◽  
Text Documents ◽  
Text Document ◽  
Document Management System ◽  
Optical Character ◽  
Electronic Document Management ◽  
Scanned Image

The article is devoted to solving the problem of document versions comparison in electronic document management systems. Systems-analogues were considered, the process of comparing text documents was studied. In order to recognize the text on the scanned image, the technology of optical character recognition and its implementation — Tesseract library were chosen. The Myers algorithm is applied to compare received texts. The software implementation of the text document comparison module was implemented using the solutions described above.

scholarly journals Neural Network with Regression Algorithms for Optical Character Recognition

2018 ◽  
Vol 7 (3.12) ◽  
pp. 341
Author(s):  
J V.Vidhya ◽  
Archit Kumar ◽  
Yashwardhan Parakh
Keyword(s):  
Neural Network ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Document Management ◽  
Modern World ◽  
Postal Service ◽  
Document Management System ◽  
Optical Character ◽  
Regression Algorithms ◽  
Learning Technique

In today's automatic and robust modern world, possibilities of optical character recognition is endless. Previously OCR was used in postal service to read address from mail, car number plate tracking, automation of bank check transfer but today it has taken document management system to whole new level. Using OCR we can convert normal hardcopy document into Searchable text. We will use deep Neural network to train systems to recognise characters in a precise manner, basically we have proposed neural network model combined with machine learning technique like gradientDescent, regression, softmax normalization which will help to increase the efficiency of the OCR. Computer will able to recognise hand written digit. We will be using Google's advanced TensorFlow to create an OCR system which will be efficient and robust in action.  

Electronic document management in chain companies of the FMCG-segment

2019 ◽  
pp. 46-51
Author(s):  
O. V. Voronova ◽  
V. A. Khareva
Keyword(s):  
Business Processes ◽  
Electronic Data Interchange ◽  
Retail Trade ◽  
Document Management ◽  
Electronic Document ◽  
Electronic Data ◽  
Document Management System ◽  
Electronic Document Management ◽  
Data Interchange ◽  
Chain Retail

This article considers the features of electronic document management at retail trade enterprises of the FMCG-segment. The paper observes the types of document flow at chain companies and examines the process of implementation of electronic document management system. The notions of “electronic document management” and “electronic data interchange” are also distinguished in the article.The paper explores positive changes caused by the introduction of electronic document management and the complexity of its implementation. The study reveals that in the Russian Federation the process of mass introduction of electronic document management in the chain retail companies of the FMCG segment has been ongoing for about ten years, though has reached the highest level of its activity in the last two years. At present day, the major part of chain retail companies in the FMCG-segment has already started to actively work with the Electronic Data Interchange system. Moreover, in recent years the number of partner-enterprises that join this system has been steadily increasing.The results of the study show that introduction of electronic document management in chain companies of the FMCG-segment allows to reduce the time spent for processing documents and to track all stages of the core business processes more effectively. It also ensures information security, improves staff discipline and the quality of service, which in its turn significantly improves management efficiency of the company in general.

scholarly journals PERANCANGAN SISTEM DOKUMENTASI ELEKTRONIK SISTEM PENJAMINAN MUTU INTERNAL MENGGUNAKAN METODE RAPID APPLICATION DEVELOPMENT

2021 ◽  
Vol 5 (1) ◽  
pp. 120
Author(s):  
Syahrizal Dwi Putra ◽  
Sabar Sukarno ◽  
Diah Aryani
Keyword(s):  
Management System ◽  
Document Management ◽  
Electronic Document ◽  
Application Development ◽  
Document Management System ◽  
Rapid Application Development ◽  
Electronic Document Management

Tujuan dari Sistem Penjaminan Mutu Pendidikan Tinggi (SPMI) adalah menjamin pemenuhan Standar Pendidikan Tinggi secara sistemik dan berkelanjutan, sehingga budaya mutu akan terus bertumbuh dan berkembang. Untuk memantau aktifitas jaminan mutu perguruan tinggi secara cepat dan tepat, maka  harus memiliki sistem dokumentasi elektronik. Electronic Document Management System (EDMS) merupakan framework sistem manajemen dokumen yang semakin spesifik untuk mengatur dan menyimpan dokumen atau laporan terkomputerisasi. Sistem dokumentasi elektronik ini dirancang dengan menggunakan metode pengembangan perangkat lunak Rapid Aplication Development (RAD). Hasilnya terbentuk model EDMS untuk SPMI, sistem manajemen pengguna dan rancangan sistem berupa fitur-fitur yang akan diterapkan pada sistem dokumentasi elektronik SPMI.

Optical Character Recognition of Indian Language Manuscripts using Convolutional Neural Networks

2021 ◽  
pp. 894-911
Author(s):  
Bhavesh Kataria, Dr. Harikrishna B. Jethva
Keyword(s):  
Neural Networks ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Short Term Memory ◽  
Short Term ◽  
Indian Language ◽  
Term Memory ◽  
Text Document ◽  
Optical Character ◽  
Long Short Term Memory

India's constitution has 22 languages written in 17 different scripts. These materials have a limited lifespan, and as generations pass, these materials deteriorate, and the vital knowledge is lost. This work uses digital texts to convey information to future generations. Optical Character Recognition (OCR) helps extract information from scanned manuscripts (printed text). This paper proposes a simple and effective solution of optical character recognition (OCR) Sanskrit Character from text document images using long short-term memory (LSTM) and neural networks of Sanskrit Characters. Existing methods focuses only upon the single touching characters. But our main focus is to design a robust method using Bidirectional Long Short-Term Memory (BLSTM) architecture for overlapping lines, touching characters in middle and upper zone and half character which would increase the accuracy of the present OCR system for recognition of poorly maintained Sanskrit literature.

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