Ruolan Zhang
ABSTRACT
Visual object detection is one of the most important aspects of the autonomous ship's perception. In order to make various deep learning-based target detection models have a unified performance evaluation standard, we provide an image dataset in various ship navigation scenarios and its corresponding target detection benchmarks, optimize the target classification strategy, and use the real navigation scene dataset to train the milestone target detection models, which effectively proves that the object detection SOTA model has uneven performance in real specific scenarios. It is difficult to realize the industrial deployment of visual perception for autonomous ship navigation.
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Index Terms
- Diversified assessment benchmark of vision dataset-based perception in ship navigation scenario
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