Use this url to cite publication: https://hdl.handle.net/20.500.14172/24642
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Detecting Maritime traffic anomalies with long-short term memory recurrent neural network
Type of publication
Tezės kitame recenzuojamame leidinyje / Theses in other peer-reviewed publication (T1e)
Type of document
type::text::conference output::conference proceedings::conference paper
Author(s)
LT | Vilniaus universitetas | LT | ||
Treigys, Povilas | Vilniaus universitetas | |||
Bernatavičienė, Jolita | Vilniaus universitetas | |||
Markevičiūtė, Jurgita | Vilniaus universitetas |
Title
Detecting Maritime traffic anomalies with long-short term memory recurrent neural network
Publisher
Vilnius : Vilnius University Press, 2019
Date Issued
Date Issued | Start Page | End Page |
---|---|---|
2019-11-25 | 89 | 89 |
Is part of
11th international workshop on data analysis methods for software systems (DAMSS 2019) : Druskininkai, Lithuania, November 28-30, 2019
Field of Science
ISBN (of the container)
9786090703243
9786090703250
eLABa
55161168
Coverage Spatial
Lietuva / Lithuania (LT)
Language
Anglų / English (en)
Date Reporting
2019
Access Rights
Atviroji prieiga / Open Access
File(s)