Research Article
Deep Learning-Based Wildfire Image Detection and Classification Systems for Controlling Biomass
Table 4
Precision analysis for RBFN-RAISR technique with existing systems.
| No. of data from dataset | CNN | R-CNN | SVM | ANN | DT | BNN | RBFN-RAISR |
| 100 | 62.78 | 76.45 | 69.23 | 79.34 | 82.98 | 88.19 | 91.67 | 200 | 63.19 | 77.13 | 70.32 | 80.45 | 83.19 | 89.43 | 91.45 | 300 | 64.55 | 78.34 | 71.32 | 81.32 | 84.23 | 89.12 | 92.19 | 400 | 65.19 | 79.13 | 72.19 | 81.45 | 84.19 | 88.13 | 93.56 | 500 | 66.98 | 79.19 | 74.89 | 81.55 | 85.12 | 87.23 | 95.87 | 600 | 67.12 | 77.23 | 75.19 | 83.98 | 86.14 | 88.45 | 94.11 | 700 | 68.33 | 78.12 | 76.12 | 82.44 | 87.45 | 89.17 | 94.19 |
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