Neural Network with Regression Algorithms for Optical Character Recognition
| Autor: | S Sriadhi, Fatkul Anam, Tonni Limbong, Maulana Arafat Lubis, Agung Purnomo, Anna Tambunan, Muhammad Irwan Padli Nasution, Choms Gary Ganda Tua Sibarani, Desi Novita |
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| Rok vydání: | 2018 |
| Předmět: |
Environmental Engineering
Artificial neural network Computer science business.industry General Chemical Engineering General Engineering Pattern recognition Optical character recognition computer.software_genre Hardware and Architecture ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Computer Science (miscellaneous) Artificial intelligence Regression algorithm business computer Biotechnology |
| Zdroj: | International Journal of Engineering & Technology. 7:341 |
| ISSN: | 2227-524X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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