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Deep Learning for Situational Awareness in a Maritime Environment

Klemm, Jannik (2022) Deep Learning for Situational Awareness in a Maritime Environment. WAW Machine Learning, 2022-11-07 - 2022-11-09, Jena, Germany. (Unpublished)

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Abstract

The general future objectives and research questions are presented. In addition, we trained a LSTM model to predict future wave heights depending on previous local weather information. For the prediction, wave heights are classified for several wave height intervals.

Item URL in elib:https://elib.dlr.de/195737/
Document Type:Conference or Workshop Item (Poster)
Title:Deep Learning for Situational Awareness in a Maritime Environment
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Klemm, JannikUNSPECIFIEDhttps://orcid.org/0009-0009-2031-6137UNSPECIFIED
Date:7 November 2022
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Unpublished
Keywords:weather time series, long short-term memory, deep learning, wave height prediction
Event Title:WAW Machine Learning
Event Location:Jena, Germany
Event Type:Workshop
Event Start Date:7 November 2022
Event End Date:9 November 2022
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Bremerhaven
Institutes and Institutions:Institute for the Protection of Maritime Infrastructures > Reslience of Maritime Systems
Deposited By: Klemm, Jannik
Deposited On:10 Nov 2023 14:05
Last Modified:24 Apr 2024 20:56

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