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Vadym Slyusar

Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine

Povitroflotsky ave., 28

Kyiv, 03049

Ukraine

  • Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine

SCHOLARLY PAPERS

4

DOWNLOADS

480

TOTAL CITATIONS

6

Scholarly Papers (4)

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1.

Improving The Model Of Object Detection On Aerial Photographs And Video In Unmanned Aerial Systems

Eastern-European Journal of Enterprise Technologies, 1 (9 (115)), 24–34 2022, doi: https://doi.org/10.15587/1729-4061.2022.252876
Number of pages: 11 Posted: 29 Apr 2022
Vadym Slyusar, Mykhailo Protsenko, Anton Chernukha, Vasyl Melkin, Oleh Biloborodov, Mykola Samoilenko, Olena Kravchenko, Halyna Kalynychenko, Anton Rohovyi and Mykhaylo Soloshchuk
Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, National University of Civil Defence of Ukraine, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, Mykolayiv National Agrarian University, Mykolayiv National Agrarian University, Mykolayiv National Agrarian University, National Technical University "Kharkiv Polytechnic Institute" and National Technical University "Kharkiv Polytechnic Institute"
Downloads 160 (472,207)

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Neural network, object detection, VisDrone 2021, Microsoft COCO, YOLOv5x, unmanned aerial system

2.

Improving a Neural Network Model for Semantic Segmentation of Images of Monitored Objects in Aerial Photographs

Eastern-European Journal of Enterprise Technologies, 6 (2 (114)), 86–95. doi: https://doi.org/10.15587/1729-4061.2021.248390
Number of pages: 10 Posted: 10 Mar 2022
Vadym Slyusar, Mykhailo Protsenko, Anton Chernukha, Vasyl Melkin, Olena Petrova, Mikhail Kravtsov, Svitlana Velma, Nataliia Kosenko, Olga Sydorenko and Maksym Sobol
Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, National University of Civil Defence of Ukraine, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, Mykolayiv National Agrarian University, Kharkiv National Automobile and Highway University, National University of Pharmacy, O. M. Beketov National University of Urban Economy in Kharkiv, National Technical University "Kharkiv Polytechnic Institute" and National Technical University "Kharkiv Polytechnic Institute"
Downloads 139 (530,816)
Citation 1

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Semantic segmentation of images, convolutional neural network, aerial photograph, unmanned aerial vehicle

3.

Improvement of the Model of Object Recognition in Aero Photographs Using Deep Convolutional Neural Networks

Eastern-European Journal of Enterprise Technologies, 5(2 (113), 6–21, 2021. doi:10.15587/1729-4061.2021.243094
Number of pages: 16 Posted: 10 Jan 2022
Vadym Slyusar, Mykhailo Protsenko, Anton Chernukha, Pavlo Kovalov, Pavlo Borodych, Serhii Shevchenko, Oleksandr Chernikov, Serhii Vazhynskyi, Oleg Bogatov and Kirill Khrustalev
Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, National University of Civil Defence of Ukraine, National University of Civil Defence of Ukraine, National University of Civil Defence of Ukraine, National University of Civil Defence of Ukraine, Kharkiv National Automobile and Highway University, Ivan Kozhedub Kharkiv National Air Force University, Kharkiv National Automobile and Highway University and Kharkiv National University of Radio Electronics
Downloads 105 (664,543)
Citation 2

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object recognition, deep convolutional neural network, aerial photograph, unmanned aerial vehicle

4.

Construction of An Advanced Method for Recognizing Monitored Objects by a Convolutional Neural Network Using a Discrete Wavelet Transform

Slyusar, V., Protsenko, M., Chernukha, A., Gornostal, S., Rudakov, S., Shevchenko, S., Chernikov, O., Kolpachenko, N., Timofeyev, V., & Artiukh, R. (2021). Eastern-European Journal of Enterprise Technologies
Number of pages: 13 Posted: 21 Oct 2021
Vadym Slyusar, Mykhailo Protsenko, Anton Chernukha, Stella Gornostal, Sergey Rudakov, Serhii Shevchenko, Oleksandr Chernikov, Nadiia Kolpachenko, Volodymyr Timofeyev and Roman Artiukh
Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine, National University of Civil Defence of Ukraine, National University of Civil Defence of Ukraine, National University of Civil Defence of Ukraine, National University of Civil Defence of Ukraine, Kharkiv National Automobile and Highway University, Kharkiv Petro Vasylenko National Technical University of Agriculture, O.M. Beketov National University of Urban Economy in Kharkiv and State Enterprise “Southern State Design and Research Institute of Aviation Industry”
Downloads 76 (830,555)
Citation 3

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neural network, discrete wavelet transform, monitored objects, unmanned aircraft system