Implementation of Multilayer Perceptron for Image Classification

Authors

  • Amnia Salma Universitas Indonesia

Keywords:

Keywords: Multi layer Perceptron, image classification, rockpaperscissor.

Abstract

Abstract. This research proposed to classify images on hands playing rockpaperscissor through hand images. We use Multi Layer Perceptron to classify. There are there class for the classification which are rock class, paper class and scissor class. Dataset for this research obtained from Kaggle Dataset. The number of datasets is 2188 images which are 712 rock images, 726 paper images and 750 scissor images. The Accuracy of this model is very good arround 95%. 

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References

Ahadi PA, Casman and Nur’aini. 2020. Pengaruh Social Distancing Pada Wabah Covid-19 Terhadap Kelompok Rentan di Indonesia. Jurnal Kebijakan Kesehatan Indonesia:JKKI. Vol.09, 61-67. Kyriazis A., Mews G., Elisabeth B., Jens A. & Ahmed MS. 2020. Physical Distancing, Children and urban Health. The Covid-19 Crisis’ impact on Children and how this could affect future urban planning and design policies. www.tandfonline.com/loi/rcah/20. Murugan Subadra, Lakshmi K. P., Sundar J., & Mathi Vathani K. 2014. Design and Implementation Of Multilayer Perceptron With OnChip Learning in Vertex-E. AASRI Procedia, 6,82-88. Ramchoun Hassan, Mohammed AJI, Youssef G., & Mohamed E. Multilayer Perceptron: Architecture Optimization and Training. International Journal of Interactive Multimedia and Artificial Intelligence Vol 4: 26-30. 2016. Rosenblat. 1958. The Perceptron: A Theory of statistical Separability in Cognitive Systems, Cornell Aeronautical Laboratory, Report No. VG-1196-G-1, January.

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Published

2021-02-28

How to Cite

Salma, A. (2021). Implementation of Multilayer Perceptron for Image Classification. Proceeding International Conference on Science and Engineering, 4, 212–215. Retrieved from https://sunankalijaga.org/prosiding/index.php/icse/article/view/660

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Articles