MACHINE LEARNING METHODS FOR IMPROVING THE QUALITY OF IMAGES FROM RAILWAY SURVEILLANCE CAMERAS

2021

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DOI 10.51889/2021-1.1728-7901.19
Data confidence 70 medium
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Abstract

The article shows the development of the methodology for changing the resolution of images obtained from CCTV cameras on railway transport. The research was carried out on the basis of the application of machine learning methods (MLM). Thanks to the implementation of this approach, it was possible to expand the functionality of the MMO. In particular, it is proposed to carry out the oversampling process with the target coefficient of information content of the image frames. This factor is applicable for both increasing and decreasing RI. This should provide a high quality resampling and, at the same time, reduce the training time for neural-like structures (NLS). The proposed solutions are characterized by a reduction in the size of the computing resources that are required for such a procedure.