This article is cited in 1 paper

IMAGE PROCESSING, PATTERN RECOGNITION

Detection of artificial fragments embedded in remote sensing images by adversarial neural networks

M. V. Gashnikov, A. V. Kuznetsov

Samara National Research University

Abstract: We investigate algorithms for detecting artificial fragments of remote sensing images gener-ated by adversarial neural networks. We consider a detector of artificial images based on the detection of a spectral artifact of generative-adversarial neural networks that is caused by a layer for en-hancing the resolution. We use the detecting algorithm to detect artificial fragments embedded in natural remote sensing images using an adversarial neural network that includes a contour generator. We use remote sensing images of various types and resolutions, whereas the substituted areas, some being not simply connected, have different sizes and shapes. We experimentally prove that the investigated spectral neural network detector has high efficiency in detecting artificial fragments of remote sensing images.

Keywords: detection of artificial fragments of images, neural networks, generative adversarial neural networks, cycle neural networks, image redefinition

Received: 15.12.2021
Accepted: 16.03.2022

DOI: 10.18287/2412-6179-CO-1064