Research Article
Deep Learning-Based Wildfire Image Detection and Classification Systems for Controlling Biomass
Table 7
Accuracy analysis for the RBFN-RAISR technique with existing systems.
| No. of data from dataset | CNN | R-CNN | SVM | ANN | DT | BNN | RBFN-RAISR |
| 100 | 61.89 | 73.98 | 68.12 | 82.56 | 79.34 | 86.31 | 91.87 | 200 | 62.56 | 72.12 | 67.34 | 83.78 | 78.98 | 86.34 | 93.65 | 300 | 63.98 | 75.34 | 69.56 | 84.12 | 81.56 | 88.45 | 94.12 | 400 | 64.12 | 76.34 | 71.22 | 84.45 | 81.24 | 89.12 | 94.87 | 500 | 65.55 | 77.12 | 71.45 | 84.23 | 81.89 | 89.45 | 95.34 | 600 | 66.45 | 78.45 | 71.67 | 85.67 | 82.45 | 90.48 | 96.12 | 700 | 67.98 | 79.89 | 72.89 | 86.13 | 82.87 | 90.56 | 97.55 |
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