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Marine vessel detection method based on feature extraction and feature weighting selection fusion

PendingCN122265870AEnhance feature expressionEnhanced feature informationBiological modelsScene recognitionData setAlgorithm
The application discloses a marine ship detection method based on feature extraction and feature weighting selection fusion. First, remote sensing ship images are collected to construct a data set. Then, a ship detection model is constructed, the remote sensing ship images are input into the model to obtain fusion features, and then the fusion features are input into a detection head of the model for detection to obtain a detection result. Then, the model is trained, the remote sensing ship images are input into the model, and after multiple rounds of training, a final model is obtained. Finally, the remote sensing ship images are input into the trained model to output ship types and positioning information. The application utilizes dynamic learning sampling point offset and modulation factors to enable convolution kernels to change according to ship shapes and enhance feature information. In the feature fusion stage, feature pyramid networks based on hierarchical scales are developed to fully utilize feature maps from different scales and enhance the feature expression capability of the model.
Owner:SANYA SCI & EDUCATION INNOVATION PARK WUHAN UNIV OF TECH