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 (Unpublished)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:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Klemm, Jannik	UNSPECIFIED	https://orcid.org/0009-0009-2031-6137	UNSPECIFIED

Date:

7 November 2022

Refereed publication:

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

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Unpublished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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