Table 8
Comparison with previous research.
| No. | References | Method Used | Accuracy Achieved |
|---|---|---|---|
| 1 | [14] | Custom 9-layer CNN | 97.20 % |
| 2 | [15] | Shallow 3-layer CNN | 97.89 % |
| 3 | [16] | Ensemble CNN + Grad-CAM visualization | 97.11–99.69 % |
| 4 | [17] | Residual VGG-19 + CLAHE | 97.73 % |
| 5 | [18] | Baseline CNN | 95.00 % |
| 6 | [19] | Transfer-learned ResNet-50 CNN | 98.00 % |
| 7 | [20] | CNN-EWC | 98-- 99.6 % |
| 8 | Proposed Model | Resnet50-EWC | 98.96 % |
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.