A ship detection algorithm for nearshore targets based on improved YOLOv7
In order to improve the detection accuracy of near-shore small target ships,a YOLO-ConSwin ship target detection algorithm based on YOLOv7 network model is proposed in this paper.ConvNext and Swin-Transformer modules are integrated in the trunk network to enhance the model's ability to capture features on a multi-scale.Introducing SimAM,a parameter-free attention mechanism,into the feature pyramid network structure enhances the sensitivity to important channel features,strengthens the weight of ship targets,and suppresses background noise.Experimental results show that the ship identification accuracy is improved by 11%compared to YOLOv7s,proving that the YOLO-ConSwin algorithm meets the requirements for detect-ing small ship targets.
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