Exploratory Analysis of MNIST Handwritten Digit for Machine Learning Modelling

Author:

Shamsuddin Mohd Razif,Abdul-Rahman Shuzlina,Mohamed Azlinah

Publisher

Springer Singapore

Reference16 articles.

1. Grother, P., Hanaoka, K.: NIST special database 19 hand printed forms and characters 2nd Edition, National Institute of Standards and Technology (2016) Available: http://www.nist.gov/srd/upload/nistsd19.pdf . Accessed 20 July 2018

2. Grother, P.: NIST special database 19 hand printed forms and characters database. National Institute of Standards and Technology, Technical report (1995). http://s3.amazonaws.com/nist-srd/SD19/1stEditionUserGuide.pdf,last . Accessed 20 July 2018

3. Kulkarni, S.R., Rajendran, B.: Spiking neural networks for handwritten digit recognition, supervised learning and network optimization (2018)

4. Kim, J., Kim, H., Huh, S., Lee, J., Choi, K.: Deep neural networks with weighted spikes. Neurocomputing (2018)

5. Cohen, G., Afshar, S., Tapson, J., van Schaik, A.: EMNIST: an extension of MNIST to handwritten letters. Comput. Vis. Pattern Recognit. (2017)

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