Abstract
The research paper presents the author’s software for automatic identification the rolling stock at marshaling yards using a neural network. Methods for processing images from several cameras, recognizing cuts, creating a fleet model and displaying this model for further display in the Russian Railway information systems have been implemented. The software was developed in the Python 3.6 programming language, using the OpenCV and Torch libraries. Based on the obtained results, a sys-tem for monitoring the track availability of the fleet formation was implemented. A method for neural network training is demonstrated using the example of recognizing cuts of a marshaling yard.
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