Classification of Pictures Using Different Algorithms

Authors

  • Zurui Chen

DOI:

https://doi.org/10.54097/hset.v9i.1725

Keywords:

machine learning; algorithms; accurate; MNIST.

Abstract

This study can be seen as an attempt of handwritten text recognition and analysis, because the dataset can be extended to a dataset including alphabets with or without the colour, and when the model can successfully learn the patterns, it can be applied to real-life applications such as scanning a handwritten document and save its text into a digital document.

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References

Birjit Gope, Sagar Pande,Nikhil Karale,et al. Handwritten Digits Identification Using Mnist Database Via Machine Learning Models. IOP Conf. Series: Materials Science and Engineering 1022 (2021) 012108

Majid Vafadar, A Convolutional Neural Network solution for MNIST dataset,February 2018 , Information on: https://www.researchgate.net/publication/339439927

Meshaal mouawad,Pattern Recognition of Handwritten Digits MNIST Dataset,2021,Information on: https://www.academia.edu/48976711

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Published

30-09-2022

Issue

Vol. 9 (2022): 4th International Conference on Computer Engineering, Information Science and Internet Technology (CII 2022)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.