Deep learning-based airport scene moving target identification method combined with ADS-B (Automatic Dependent Surveillance-Broadcast) information
A technology of ADS-B and moving targets, applied in neural learning methods, character and pattern recognition, computer components, etc., can solve problems such as algorithm display results are not intuitive enough, information redundancy, and the aircraft is stationary on the apron, etc., to achieve effective The effect of scene monitoring scheme and improvement of detection accuracy
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[0034] The specific embodiments of the present invention are described below to facilitate those skilled in the art to understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes Such changes are obvious within the spirit and scope of the present invention as defined and determined by the appended claims, and all inventions and creations utilizing the inventive concept are within the scope of protection.
[0035] A deep learning-based airport scene moving target recognition method combined with ADS-B information, such as figure 1 shown, including the following steps:
[0036]S1. Decode the ADS-B information, and use the three-dimensional data returned by the aircraft and the position of the camera to correspond the ADS-B data to the two-dimensional image;
[0037] S2, label the scene surveillance video sequences in the airport scene surveil...
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