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Robustness Study of a Deep Convolutional Neural Network for Vehicle Detection in Aerial Imagery

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Abstract

The robustness of a deep convolutional neural network for vehicle detection in aerial imagery is analyzed. The study allows us to evaluate detection quality and correctness of a trained neural network. The method of improving noise immunity for an object detection system in aerial imagery is proposed.

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FUNDING

This work was supported by the Russian Science Foundation, grant no. 18-72-10118.

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Authors and Affiliations

  1. Moscow Technical University of Communications and Informatics, 111024, Moscow, Russia

    O. V. Ilina & M. V. Tereshonok

  2. Moscow Institute of Physics and Technology (National Research University), 141701, Dolgoprudnyi, Moscow oblast, Russia

    M. V. Tereshonok

Authors
  1. O. V. Ilina
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  2. M. V. Tereshonok
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Correspondence to M. V. Tereshonok.

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Ilina, O.V., Tereshonok, M.V. Robustness Study of a Deep Convolutional Neural Network for Vehicle Detection in Aerial Imagery. J. Commun. Technol. Electron. 67, 164–170 (2022). https://doi.org/10.1134/S1064226922020048

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  • DOI: https://doi.org/10.1134/S1064226922020048

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