A comparison of embedded deep learning methods for person detection

Chloe Eunhyang Kim, Mahdi Maktab Dar Oghaz, Jiri Fajtl, Vasileios Argyriou, Paolo Remagnino

    Research output: Contribution to conferencePaperpeer-review

    Original languageEnglish
    Publication statusPublished - Feb 2019
    Event14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Prague, Czech Republic
    Duration: 25 Feb 201927 Feb 2019

    Conference

    Conference14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
    Period25/02/1927/02/19

    Bibliographical note

    Note: Published in: Tremeau, Alain, Farinella, Giovanni Maria, Braz, Jose (eds.) (2019) Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Setubal, Portugal : Science and Technology Publications. Volume 5, pp.459-465. ISBN 9789897583544. This work is co-funded by the EU-H2020 within the MONICA project under grant agreement number 732350. The Titan X Pascal used for this research was donated by NVIDIA.

    Keywords

    • Computer science and informatics
    • A comparison of embedded deep learning methods for person detection

      Kim, C. E., Dar Oghaz, M. M., Fajtl, J., Argyriou, V. & Remagnino, P., Feb 2019, Published in: Tremeau, Alain, Farinella, Giovanni Maria, Braz, Jose (eds.) (2019) Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Setubal, Portugal : Science and Technology Publications. Volume 5, pp.459-465. ISBN 9789897583544. This work is co-funded by the EU-H2020 within the MONICA project under grant agreement number 732350. The Titan X Pascal used for this research was donated by NVIDIA..

      Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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