Generation method of synthetic training data for mobile OCR system
| Autor: | Alexander Sheshkus, Alexander V. Gayer, Yulia S. Chernyshova |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Training set
business.industry Computer science Training (meteorology) 02 engineering and technology Machine learning computer.software_genre Synthetic data 03 medical and health sciences 0302 clinical medicine 030221 ophthalmology & optometry 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | ICMV |
| DOI: | 10.1117/12.2310119 |
| Popis: | This paper addresses one of the fundamental problems of machine learning - training data acquiring. Obtaining enough natural training data is rather difficult and expensive. In last years usage of synthetic images has become more beneficial as it allows to save human time and also to provide a huge number of images which otherwise would be difficult to obtain. However, for successful learning on artificial dataset one should try to reduce the gap between natural and synthetic data distributions. In this paper we describe an algorithm which allows to create artificial training datasets for OCR systems using russian passport as a case study. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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