Issue |
E3S Web Conf.
Volume 399, 2023
International Conference on Newer Engineering Concepts and Technology (ICONNECT-2023)
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|
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Article Number | 04027 | |
Number of page(s) | 8 | |
Section | Computer Science | |
DOI | https://doi.org/10.1051/e3sconf/202339904027 | |
Published online | 12 July 2023 |
Accurate Biometric Palm Print Recognition Using ResNet50 algorithm Over X Gradient Boosting Algorithm
Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India, Pincode: 602105
* Corresponding Author: Kishoressvcsv@gmail.com
The aim of this research is to enhance the accuracy of biometric palm print identification by using the Novel ResNet50 Algorithm as compared to the X Gradient Boosting. Materials and Methods: In this study, the ResNet50 and X Gradient Boosting algorithms were compared using a sample size of 10 for each algorithm, resulting in a total sample size of 20. The comparison was carried out with a G Power of 0.8 and a confidence interval (CI) of 95% to ensure statistical significance. For this study the Birjand University Mobile Palmprint Database (BMPD) dataset was collected from the Kaggle repository, which includes a total of 1640 images containing both left and right-hand palmprints. Result: According to the results, the ResNet50 algorithm achieved a higher accuracy rate (94.7%) compared to the X Gradient Boosting algorithm (92.4%) in identifying and measuring the images. The statistical analysis indicated a significant difference between the Novel ResNet50 algorithm and X Gradient Boosting, with a pvalue of 0.003 (Independent sample T-test p<0.05). This suggests that the ResNet50 algorithm outperformed the X Gradient Boosting algorithm in this experiment. According to the study’s findings, ResNet50 is more effective in accurately identifying biometric palm prints compared to X Gradient Boosting.
Key words: Biometric / Fingerprint / Novel ResNet50 / Palm Print / Technology / XGradient Boosting
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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