December 8, 2025SymmetryOpen Access

Research on Fouling Shellfish on Marine Aquaculture Cages Detection Technology Based on an Improved Symmetric Faster R-CNN Detection Algorithm

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Average precision reached 94.27%, showing significant improvement in detection capabilities.
This approach utilizes a residual network architecture for better feature extraction during detection.
Optimized anchor box dimensions and IoU threshold enhance the adaptation to object scale.
Potential for automation in cleaning processes using autonomous underwater vehicles is highlighted.

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Methodology demonstrates enhanced object detection accuracy of fouling shellfish in aquaculture, indicating efficient use of underwater vehicles.

Zhu et al. (2025) studied this question.

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Methodology demonstrates enhanced object detection accuracy of fouling shellfish in aquaculture, indicating efficient use of underwater vehicles.