Improved Faster R-CNN Algorithm for Sea Object Detection Under Complex Sea Conditions
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Jul 13, 2020
About this article
Published Online: Jul 13, 2020
Page range: 76 - 82
DOI: https://doi.org/10.21307/ijanmc-2020-020
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© 2020 Liu Yabin et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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VALUES OF MAIN NETWORK PARAMETERS
| Parameters | Values | Parameters | Values |
|---|---|---|---|
| LEARNING_RATE | le-3 | Bateh_size | 256 |
| Anchor_Scales | [8,16,32] | Anchor_RATIOS | [0.7, 1.2, 1.3, 2.9] |
| ITERS | 85000 | num_classes | 6 |
| SOFT_NMS | 1 |
COMPARISON OF DETECTION RESULTS OF THREE NETWORK STRUCTURES
| Detection method | Passenger_ ship | Cargo_ship | Container_ ship | Aircraft_ ship | War_ship | mAP |
|---|---|---|---|---|---|---|
| VGG-16 structure | 50.9% | 80.6% | 92.4% | 98.1% | 92.8% | 82.96% |
| ResNet101 structure | 54.1% | 81.0% | 92.8% | 99.3% | 93.0% | 84.04% |
| improved ResNet101 structure | 66.9% | 82.3% | 93.65% | 99.51% | 93.9% | 87.25% |
ANCHOR_RATIOS FOR DIFFERENT K VALUES
| number | K=1 | K=2 | K=3 | K=4 | K=5 | K=6 | K=7 |
|---|---|---|---|---|---|---|---|
| 0.6 | 1.3 | 0.5 | 0.7 | 0.6 | 0.5 | 0.5 | |
| - | 1.4 | 1.2 | 1.2 | 1.2 | 0.7 | 0.6 | |
| - | - | 1.6 | 1.3 | 1.3 | 1.2 | 1.1 | |
| - | - | 2.9 | 1.7 | 1.3 | 1.2 | ||
| - | - | - | - | 2.6 | 2.4 | 1.8 | |
| - | - | - | - | - | 3 | 2.1 | |
| - | - | - | - | - | - | 2.9 | |
| 83.84 | 84.3 | 84.32 | 84.98 | 84.29 | 84.57 | 84.34 | |
| 503 | 510 | 515 | 518 | 524 | 515 | 517 |