This paper introduces a comparison study between SVM and a convolutional neural network for automatic train moving recognition by exploiting distributed acoustic sensing data. The results show the performance of each of the two methods for such a goal.
We demonstrate the reliability of two coherent detection DAS systems on detecting vibrations generated in a railway environment. Systems have been validated by accelerometers based measurements. A demonstration of a rail vehicle tracking is also performed.
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