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

Rashid, AH; Razzak, Imran; Tanveer, M; Robles-Kelly, Antonio

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

conference contribution

posted on 2024-06-05, 06:31 authored by AH Rashid, Imran Razzak, M Tanveer, Antonio Robles-KellyAntonio Robles-Kelly

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

History

Volume

1333

Pagination

172-179

Location

Online from Bangkok, Thailand

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)

Yang H, Pasupa K, Leung AC-S, Kwok JT, Chan JH, King I

Title of proceedings

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

Event

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

Publisher

Springer

Place of publication

Cham, Switzerland

Series

Neural Information Processing International Conference

Usage metrics

Keywords

Rip currents Rip detection CNN Autoencoder Anomaly detection

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

History

Volume

Pagination

Location

Start date

End date

ISSN

eISSN

ISBN-13

Notes

Publication classification

Editor/Contributor(s)

Title of proceedings

Event

Publisher

Place of publication

Series

Usage metrics

Categories

Keywords

Licence

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