Research Article
Moving Vehicle Detection and Classification Using Gaussian Mixture Model and Ensemble Deep Learning Technique
Table 6
Comparative analysis between the proposed and the existing techniques.
| Algorithm | Dataset | Precision (%) | Recall (%) | Accuracy (%) |
| GAN-based deep ensemble technique [13] | MIO-TCD | 96.41 | — | — | Tiny YOLO with SVM [15] | BIT Vehicle | 97.90 | 99.60 | — | Semisupervised CNN model [19] | BIT Vehicle | — | — | 88.11 | PCN with softmax classifier [21] | BIT Vehicle | — | — | 88.52 | TC-SF-CNNLS [22] | BIT Vehicle | 90.52 | 90.41 | 93.80 | Ensemble deep learning technique | MIO-TCD | 99.12 | 99.69 | 99.13 | BIT Vehicle | 98.24 | 99.72 | 99.28 | Combined | 99.27 | 99.77 | 99.32 |
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