Deep belief network based approach to recognize handwritten Kannada characters using distributed average of gradients
| Autor: | K. Srikanta Murthy, S. Karthik |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications 02 engineering and technology computer.software_genre language.human_language Field (computer science) Kannada Deep belief network ComputingMethodologies_PATTERNRECOGNITION Pattern recognition (psychology) 0202 electrical engineering electronic engineering information engineering Feature (machine learning) language 020201 artificial intelligence & image processing Artificial intelligence business computer Computer communication networks Software Natural language processing |
| Zdroj: | Cluster Computing. 22:4673-4681 |
| ISSN: | 1573-7543 1386-7857 |
| Popis: | Even though various advances have been made in recent years, the recognition of handwritten characters is still an open challenge in the Pattern Recognition field. Different approaches are invented for the recognition of printed characters of Indian languages. However, few attempts are done for the recognition of handwritten characters. A high degree of recognition accuracy for the handwritten characters is yet to be achieved. In this paper, a new approach based on deep belief network with the distributed average of gradients feature is presented for the recognition of isolated handwritten characters of Kannada, which is the official language of Karnataka state in India. In the proposed methods, a better accuracy is achieved. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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