e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos

Tariq Rahim; Arslan Musaddiq; Dong Seong Kim

doi:10.1109/ICUFN49451.2021.9528627

e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos

Tariq Rahim, Arslan Musaddiq, Dong Seong Kim

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 financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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	48-52
DOIs	https://doi.org/10.1109/ICUFN49451.2021.9528627
Publication status	Published - 17 Aug 2021

Bibliographical note

Note: This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology.
Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762.

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/ICUFN49451.2021.9528627

https://doi.org/10.1109/ICUFN49451.2021.9528627

1 Paper

e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos
Rahim, T., Musaddiq, A. & Kim, D.-S., 17 Aug 2021.
Research output: Contribution to conference › Paper › peer-review

Cite this

Rahim, T., Musaddiq, A., & Kim, D. S. (2021). e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos. In This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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. 48-52) https://doi.org/10.1109/ICUFN49451.2021.9528627

Rahim, Tariq ; Musaddiq, Arslan ; Kim, Dong Seong. / e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos. This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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). 2021. pp. 48-52

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Rahim, T, Musaddiq, A & Kim, DS 2021, e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos. in This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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. 48-52. https://doi.org/10.1109/ICUFN49451.2021.9528627

e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos. / Rahim, Tariq; Musaddiq, Arslan; Kim, Dong Seong.
This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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). 2021. p. 48-52.

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

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T1 - e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos

AU - Rahim, Tariq

AU - Musaddiq, Arslan

AU - Kim, Dong Seong

N1 - Note: This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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 - 2021/8/17

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DO - 10.1109/ICUFN49451.2021.9528627

M3 - Conference contribution

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BT - This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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 -

Rahim T, Musaddiq A, Kim DS. e-health and resource management scheme for a deep learning-based detection of tumor in wireless capsule endoscopy videos. In This research was financially supported by the MSIT (Ministry of Science, ICT), Korea, under the Grand Information Technology Research Center support program [grant number: IITP-2020- 2020-0-01612] supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation), and Priority Research Centers Program [grant number: 2018R1A6A1A03024003] through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. Published in: Proceedings of 2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN), Piscataway, U.S. : Institute of Electrical and Electronics Engineers, pp. 48-52, ISSN: 2165-8536, ISBN: 9781728164762. 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). 2021. p. 48-52 doi: 10.1109/ICUFN49451.2021.9528627