A pragmatic convolutional bagging ensemble learning for recognition of Farsi handwritten digits

Author:

Nanehkaran Y. A.,Chen Junde,Salimi Soheil,Zhang Defu

Funder

the National Natural Science Foundation of China

the Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Reference40 articles.

1. Sajedi H, Bahador M (2016) Persian handwritten number recognition using adapted framing feature and support vector machines. Int J Comput Intell Appl 15(1):165–180

2. Karimi H, Esfahanimehr A, Mosleh M, Salehpour S, Medhati O (2015) Persian handwritten digit recognition using ensemble classifiers. Procedia Comput Sci 73(1):416–425

3. Khosravi H, Kabir E (2006) Introduction of Two Fast and Effective Features for Handwritten Farsi Digit Recognition. In: 2006 4th Iranian Conference on Machine Vision and Image Processing (MVIP), pp 87–95

4. Jain V, Dubey A, Gupta A, Sharma S (2016) Comparative Analysis of Machine Learning Algorithms in OCR. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), IEEE, pp 1089–1092

5. Chaudhary D, Sharma K (2019) Hindi Handwritten Character Recognition Using Deep Convolution Neural Network. In: 2019 6th International Conference on Computing for Sustainable Global Development (INDIACom), IEEE, pp 961–965

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