The thesis includes the problem description, development and testing of a convolutional neural network for single image super-resolution in digital forensics. Insufficient resolution of images and other image digital evidence is a common occurrence in the field of digital forensics. This paper presents previously developed solutions for single image super-resolution using Deep Learning based on neural networks. It then describes the implementation of a solution for quality enhancement in low-resolution images of human faces using convolutional neural network and the comparison of the solution results with existing solutions.
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