Research Article
Convolutional Neural Network Based Vehicle Classification in Adverse Illuminous Conditions for Intelligent Transportation Systems
Table 4
Performance metrics of proposed system on self-constructed dataset.
| Class | Accuracy | Error rate | Specificity | Precision | Recall | F1 score |
| Bus | 99.48 | 0.52 | 99.90 | 99.4852 | 99.13 | 99.3072 | Car | 99.68 | 0.32 | 99.94 | 99.6832 | 99.68 | 99.6816 | Motorbike | 99.08 | 0.92 | 99.82 | 99.0832 | 99.08 | 99.0816 | Rickshaw | 100.0 | 0.00 | 100.0 | 100.000 | 99.83 | 99.9149 | Truck | 100.0 | 0.00 | 100.0 | 100.000 | 99.48 | 99.7393 | Van | 99.65 | 0.35 | 99.94 | 99.6525 | 99.65 | 99.6512 | Total: | 99.65 | 0.35 | 99.93 | 99.65 | 99.48 | 99.56 |
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