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RipNet: a lightweight one-class deep neural network for the identification of RIP currents

conference contribution
posted on 2020-01-01, 00:00 authored by A H Rashid, Imran RazzakImran Razzak, M Tanveer, Antonio Robles-KellyAntonio Robles-Kelly
RipNet: a lightweight one-class deep neural network for the identification of RIP currents

History

Event

Neural Information Processing. International Conference (27th : 2020 : Online from Bangkok, Thailand)

Volume

1333

Series

Neural Information Processing International Conference

Pagination

172 - 179

Publisher

Springer

Location

Online from Bangkok, Thailand

Place of publication

Cham, Switzerland

Publisher DOI

Start date

2020-11-18

End date

2020-11-22

ISSN

1865-0929

eISSN

1865-0937

ISBN-13

9783030638221

Notes

This conference was originally scheduled to be held in Bangkok, Thailand, however due to the 2020 COVID Pandemic, the event was held online.

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

H Yang, K Pasupa, A Leung, J Kwok, J Chan, I King

Title of proceedings

ICONIP 2020 : Proceedings of the 27th International Conference on Neural Information Processing 2020

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    Research Publications

    Categories

    Keywords

    Rip currentsRip detectionCNNAutoencoderAnomaly detectionArtificial Intelligence and Image Processing

    Licence

    All Rights Reserved

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