Advances, Systems and Applications
Table 7 Related work and comparison of exiting work with accuracy
Author | Year | Method | Accuracy |
|---|---|---|---|
K. Zhang, X. H. Liang, M. Baura, R. X. Lu, and X. M. Shen [45] | 2022 | Deep Convolutional Network-based Pipeline | 98.40% |
V. Roussev and S. McCulley [41] | 2021 | Ensemble system of Deep Convolutional Neural Network | 93.28% |
A. Sathya and S. K. S. Raja [42] | 2020 | Support Vector Machine | 93.33% |
B. Kakkar, P. Johri, Y. Kumar, H. Park, Y. Son, and J. Shafi [43] | 2021 | Convolutional Neural Network | 95.23% |
A. Tembhare, S. S. Chakkaravarthy, D. Sangeetha, V. Vaidehi, and M. V. Rathnam [44] | 2022 | Lemperl Ziv Markow Algorithm | 96.8% |
Proposed work | - | Hybrid Method | 98.98% |