Railway intrusion foreign matter unmanned aerial vehicle detection method, device and system based on deep learning
A technology of deep learning and detection methods, applied in railway signal and security, motor vehicles, remote control aircraft, etc., can solve the problems of difficult design of image recognition algorithms, affecting the efficiency of recognition, and large total railway mileage, etc. performance and operational efficiency, reducing algorithm complexity, and efficient foreign object detection
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[0074] The present invention is further described below with reference to the accompanying drawings and specific embodiments of the specification, but will not limit the scope of the invention.
[0075] Such as figure 1 As shown, the steps of this embodiment based on deep learning rail-off foreign object drone detecting methods include:
[0076] S1. Real-time access to video image data along the railway to be tested by the drone real-time;
[0077] S2. Use a deep learning-based target detection model to detect whether there is foreign matter in the video image data, when the target foreign body is detected, the transfer is performed step S3;
[0078] S3. Use a deep learning target detection model to extract the railway limit in the target video frame existing target foreign matter, the railway limit is the contour that does not allow foreign matter invading on the railway, determines whether the target foreign body invades the railway limit according to the position of the target ...
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