Shahid, M, Munir, K, Muneer, S, Mutiullah, M, Jarrah, M and Farooq, U (2022) Implementation of ML Algorithm for Mung Bean Classification using Smart Phone. In: 2022 International Conference on Business Analytics for Technology and Security (ICBATS), 16-17 Feb. 2022, Dubai, United Arab Emirates.
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This work is an extension of my work presented a robust and economically efficient method for the discrimination of four Mung-Beans varieties based on quantitative parameters, Due to the advancement of technology day by day users try to find the solutions to their daily life problems using smartphones but still there is limited resources are available in smartphone concerning computing power and memory so there is need to find the best classifier which can classify the Mung-Beans using already suggested features in previous work with minimum memory requirements and computational power. For achieving the goal of this study, we take the experiments on various supervised classifiers which have simple architecture and calculations and give the robust performance on the most relevant 10 suggested features are selected by Fisher Co-efficient, Probability of Error, Mutual Information, and wavelet features. After the analysis, we replace the Artificial Neural Network and Deep learning with such a classifier which gives approximately the same classification results as the above classifier but is efficient in terms of resources and time complexity. This classifier is easily implemented in the smartphone environment.
Affiliation: | Skyline University College |
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SUC Author(s): | Jarrah, M |
All Author(s): | Shahid, M, Munir, K, Muneer, S, Mutiullah, M, Jarrah, M and Farooq, U |
Item Type: | Conference or Workshop Item (Paper) |
Uncontrolled Keywords: | Mung-Beans, Textural Features, Fisher’s Coefficient, Linear Discriminant, Artificial Neural Network |
Subjects: | B Information Technology > BL Machine Learning |
Divisions: | Skyline University College > School of IT |
Depositing User: | Mr Veeramani Rasu |
Date Deposited: | 25 May 2022 14:49 |
Last Modified: | 25 May 2022 14:49 |
URI: | https://research.skylineuniversity.ac.ae/id/eprint/239 |
Publisher URL: | https://doi.org/10.1109/ICBATS54253.2022.9759090 |
Publisher OA policy: | |
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