Efficiency of YOLO neural network models applied for object recognition in radar images

Alena S. Krasnoperova; Alexander S. Tverdokhlebov; Alexey A. Kartashov; Vladislav I. Weber; Vladimir Y. Kuprits

Russian Technological Journal
Rossiiskii Tekhnologicheskii Zhurnal

ISSN 2782-3210 (Print)
ISSN 2500-316X (Online)

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Krasnoperova A.S., Tverdokhlebov A.S., Kartashov A.A., Weber V.I., Kuprits V.Y. Efficiency of YOLO neural network models applied for object recognition in radar images. Russian Technological Journal. 2025;13(4):25-36. https://doi.org/10.32362/2500-316X-2025-13-4-25-36. EDN: WVWVCJ

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ISSN 2782-3210 (Print)
ISSN 2500-316X (Online)

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About the Authors

Alena S. Krasnoperova
Tomsk State University of Control Systems and Radioelectronics
Russian Federation

Alena S. Krasnoperova, Engineer of the Student Design Bureau of Intelligent Radio Engineering Systems, Department of Radio Engineering Systems

40, Lenina pr., Tomsk, 634050

Alexander S. Tverdokhlebov
Tomsk State University of Control Systems and Radioelectronics
Russian Federation

Alexander S. Tverdokhlebov, Engineer of the Student Design Bureau of Intelligent Radio Engineering Systems, Department of Radio Engineering Systems

40, Lenina pr., Tomsk, 634050

Alexey A. Kartashov
Tomsk State University of Control Systems and Radioelectronics
Russian Federation

Alexey A. Kartashov, Engineer of the Student Design Bureau of Intelligent Radio Engineering Systems, Department of Radio Engineering Systems

40, Lenina pr., Tomsk, 634050

Vladislav I. Weber
Tomsk State University of Control Systems and Radioelectronics
Russian Federation

Vladislav I. Weber, Postgraduate Student, Assistant, Department of Radio Engineering Systems

40, Lenina pr., Tomsk, 634050

Vladimir Y. Kuprits
Tomsk State University of Control Systems and Radioelectronics
Russian Federation

Vladimir Y. Kuprits, Cand. Sci. (Eng.), Associate Professor, Head of the Student Design Bureau of Intelligent Radio Engineering Systems, Department of Radio Engineering Systems

40, Lenina pr., Tomsk, 634050

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