Deep learning innovations in South Korean maritime navigation: Enhancing vessel trajectories prediction with AIS data

• Umar Zaman ,

  Contributed equally to this work with: Umar Zaman, Junaid Khan

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft

  Affiliation Department of Computer Engineering, Chungnam National University, Daejeon, South Korea

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• Junaid Khan ,

  Contributed equally to this work with: Umar Zaman, Junaid Khan

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft

  * E-mail: sclkim@cnu.ac.kr (KK); junaidstopi1@gmail.com (JK)

  Affiliation Department of Environmental IT Engineering, Chungnam National University, Daejeon, South Korea

  https://orcid.org/0000-0002-2393-3132

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• Eunkyu Lee,

  Roles Validation, Writing – review & editing

  Affiliations Department of Computer Engineering, Chungnam National University, Daejeon, South Korea, Autonomous Ship Research Center, Samsung Heavy Industries, Daejeon, South Korea

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• Awatef Salim Balobaid,

  Roles Software, Writing – review & editing

  Affiliation Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia

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• R. Y. Aburasain,

  Roles Methodology, Writing – review & editing

  Affiliation Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia

  https://orcid.org/0009-0003-5786-8011

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• Kyungsup Kim

  Roles Conceptualization, Data curation, Investigation, Project administration, Resources, Supervision

  * E-mail: sclkim@cnu.ac.kr (KK); junaidstopi1@gmail.com (JK)

  Affiliations Department of Computer Engineering, Chungnam National University, Daejeon, South Korea, Department of Environmental IT Engineering, Chungnam National University, Daejeon, South Korea

  https://orcid.org/0000-0002-0166-1439

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