Performance evaluation of classifiers for the recognition of offline handwritten Gurmukhi characters and numerals: a study-Reference-Cited by-同舟云学术

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Performance evaluation of classifiers for the recognition of offline handwritten Gurmukhi characters and numerals: a study

Published:2019-06-11 Issue:3 Volume:53 Page:2075-2097
ISSN:0269-2821
Container-title:Artificial Intelligence Review
language:en
Short-container-title:Artif Intell Rev

Author:

Kumar Munish,Jindal M. K.,Sharma R. K.,Jindal Simpel Rani

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Link

http://link.springer.com/content/pdf/10.1007/s10462-019-09727-2.pdf

Reference55 articles.

1. Amin A, Singh S (1998) Recognition of hand-printed Chinese characters using decision trees/machine learning C4.5 system. Pattern Anal Appl 1(2):130–141

2. Anil R, Manjusha K, Kumar SS, Soman KP (2015) Convolutional neural networks for the recognition of Malayalam characters. In: Proceedings of the 3rd international conference on frontiers of intelligent computing: theory and applications (FICTA), pp 493–500

3. Bhowmik TK, Bhattacharya U, Parui SK (2004) Recognition of Bangla handwritten characters using an MLP classifier based on stroke features. In: Proceedings of international conference on neural information processing (ICONIP’04), pp 814–819

4. Blue JL, Candela GT, Grother PJ, Chellappa R, Wilson CL (1994) Evaluation of pattern classifiers for fingerprint and OCR applications. Pattern Recognit 27(4):485–501

5. Breiman L (2001) Random forests. Mach Learn 45(1):5–32

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