Deep Learning-Empowered Unsupervised Maritime Anomaly Detection

Lingxuan Weng; Maohan Liang; Ruobin Gao; Zhong Shuo Chen

doi:10.1007/978-981-99-8178-6_15

Deep Learning-Empowered Unsupervised Maritime Anomaly Detection

Lingxuan Weng, Maohan Liang, Ruobin Gao, Zhong Shuo Chen^*

^*Corresponding author for this work

School of Intelligent Finance and Business

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

Original language	English
Title of host publication	Communications in Computer and Information Science
Subtitle of host publication	Neural Information Processing. ICONIP 2023.
Publisher	Springer Singapore
Volume	1967
ISBN (Electronic)	978-981-99-8178-6
ISBN (Print)	978-981-99-8177-9
DOIs	https://doi.org/10.1007/978-981-99-8178-6_15
Publication status	Published - 30 Nov 2023

Access to Document

10.1007/978-981-99-8178-6_15

Cite this

@inproceedings{a734e34e679f41afa3546aa0040be394,

title = "Deep Learning-Empowered Unsupervised Maritime Anomaly Detection",

author = "Lingxuan Weng and Maohan Liang and Ruobin Gao and Chen, {Zhong Shuo}",

year = "2023",

month = nov,

day = "30",

doi = "10.1007/978-981-99-8178-6_15",

language = "English",

isbn = "978-981-99-8177-9",

volume = "1967",

booktitle = "Communications in Computer and Information Science",

publisher = "Springer Singapore",

}

TY - GEN

T1 - Deep Learning-Empowered Unsupervised Maritime Anomaly Detection

AU - Weng, Lingxuan

AU - Liang, Maohan

AU - Gao, Ruobin

AU - Chen, Zhong Shuo

PY - 2023/11/30

Y1 - 2023/11/30

UR - https://link.springer.com/chapter/10.1007/978-981-99-8178-6_15

U2 - 10.1007/978-981-99-8178-6_15

DO - 10.1007/978-981-99-8178-6_15

M3 - Conference Proceeding

SN - 978-981-99-8177-9

VL - 1967

BT - Communications in Computer and Information Science

PB - Springer Singapore

ER -

Deep Learning-Empowered Unsupervised Maritime Anomaly Detection

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Other files and links

Asia Pacific Neural Network Society (APNNS) (External organisation)

The 30th International Conference on Neural Information Processing (ICONIP 2023)