Accurate Biometric Palm Print Recognition Using ResNet50 algorithm Over X Gradient Boosting Algorithm
| Autor: | Kumar H. Kishore, Kumar S. Ashok |
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| Jazyk: | English<br />French |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | E3S Web of Conferences, Vol 399, p 04027 (2023) |
| Druh dokumentu: | article |
| ISSN: | 2267-1242 53829107 |
| DOI: | 10.1051/e3sconf/202339904027 |
| Popis: | 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 |
| Databáze: | Directory of Open Access Journals |
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