Real-time UAV detection based on deep learning network

Syed Ali Hassan; Tariq Rahim; Soo Young Shin

doi:10.1109/ICTC46691.2019.8939564

Real-time UAV detection based on deep learning network

Syed Ali Hassan
, Tariq Rahim
, Soo Young Shin

Kumoh National Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Original language	English
Title of host publication	This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE)
Pages	630-632
DOIs	https://doi.org/10.1109/ICTC46691.2019.8939564
Publication status	Published - 16 Oct 2019

Bibliographical note

Note: This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003]
Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940.

Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE)

Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE)

Keywords

Computer science and informatics

Access to Document

10.1109/ICTC46691.2019.8939564

https://doi.org/10.1109/ICTC46691.2019.8939564

1 Paper

Real-time UAV detection based on deep learning network
Hassan, S. A., Rahim, T. & Shin, S. Y., 16 Oct 2019.
Research output: Contribution to conference › Paper › peer-review

Cite this

Hassan, S. A., Rahim, T., & Shin, S. Y. (2019). Real-time UAV detection based on deep learning network. In This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) (pp. 630-632) https://doi.org/10.1109/ICTC46691.2019.8939564

Hassan, Syed Ali ; Rahim, Tariq ; Shin, Soo Young. / Real-time UAV detection based on deep learning network. This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE). 2019. pp. 630-632

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title = "Real-time UAV detection based on deep learning network",

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author = "Hassan, \{Syed Ali\} and Tariq Rahim and Shin, \{Soo Young\}",

note = "Note: This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information \& communications Technology Planning \& Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE)",

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doi = "10.1109/ICTC46691.2019.8939564",

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booktitle = "This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information \& communications Technology Planning \& Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE)",

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Hassan, SA, Rahim, T & Shin, SY 2019, Real-time UAV detection based on deep learning network. in This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE). pp. 630-632. https://doi.org/10.1109/ICTC46691.2019.8939564

Real-time UAV detection based on deep learning network. / Hassan, Syed Ali; Rahim, Tariq; Shin, Soo Young.
This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE). 2019. p. 630-632.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Real-time UAV detection based on deep learning network

AU - Hassan, Syed Ali

AU - Rahim, Tariq

AU - Shin, Soo Young

N1 - Note: This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE)

PY - 2019/10/16

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KW - Computer science and informatics

U2 - 10.1109/ICTC46691.2019.8939564

DO - 10.1109/ICTC46691.2019.8939564

M3 - Conference contribution

SP - 630

EP - 632

BT - This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE)

ER -

Hassan SA, Rahim T, Shin SY. Real-time UAV detection based on deep learning network. In This research was supported by the MSIT (Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program [grant number: IITP-2019-2014-1-00639] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation); and by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education Science and Technology [grant number: 2018R1A6A1A03024003] Published in: 2019 International Conference on Information and Communication Technology Convergence (ICTC). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. pp. 630-632. ISSN: 2162-1233 ISBN: 9781728108940. Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE) Organising Body: Korean Institute of Communications and Information Sciences (KICS),The Institute of Electrical and Electronics Engineers (IEEE). 2019. p. 630-632 doi: 10.1109/ICTC46691.2019.8939564