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publicationDate 2021-03-26-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-112560671-A
titleOfInvention Ship detection method based on rotating convolutional neural network
abstract A ship detection method based on a rotating convolutional neural network relates to a ship detection method. The purpose of the present invention is to solve the problem that the characteristic information of the existing sea surface ships is disturbed or even submerged. The process is: 1. Generate a convolutional neural network feature map according to the input image; 2. Build a multi-scale feature pyramid network, extract features from the feature map, and map to generate anchors of different sizes; 3. Classify and filter out candidate frames; 4. Use Rotate the ellipse bounding box to replace the candidate box for regression prediction; 5. Calculate the loss function of the RPN; 6. Screen the output RoI Align; Positioning and regression of the direction of the bow; 8. Input the image of the ship to be tested into the trained network model to obtain the classification result. The invention is used in the field of ship detection.
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