The maritime domain is rapidly adopting deep learning techniques for diverse applications, including vessel detection, maritime traffic monitoring, anomaly detection, and autonomous navigation. Despite promising advancements, real-world deployment faces critical challenges such as data scarcity, domain shift, multimodal data fusion, and explainability. This special session aims to bring together researchers and practitioners to discuss recent developments, share challenges, and explore emerging opportunities in applying deep learning to maritime problems. The call for ideas invites academics and practitioners to submit proposals for  maritime applications of deep learning techniques: challenges and opportunities.

This special session focuses on the intersection of deep learning techniques and maritime applications, addressing both theoretical advances and practical deployments. Topics of interest include but are not limited to: 

•  Deep learning techniques for vessel detection and classification in satellite and drone imagery  

• Anomaly detection in maritime traffic using spatiotemporal data  

• Autonomous navigation and path planning for vessels using reinforcement learning and imitation learning techniques 

• Sensor fusion and multimodal learning techniques for maritime environments  

• Handling imbalanced, limited, and noisy maritime datasets  

• Explainable AI (XAI) and trustworthy deep learning techniques in safety-critical maritime systems  

• Domain adaptation and generalization for maritime environments  

• Real-time deep learning solutions for maritime surveillance 

The session encourages submissions from academia, industry, and governmental bodies addressing real-world challenges, datasets, and solutions. 

 Journal Publication:  A selected set of top-quality papers may be invited to submit full papers to a special issue.

Best Paper: All the regular papers will be considered for the BEST PAPER AWARD 

The maritime domain is rapidly adopting deep learning techniques for diverse applications, including vessel detection, maritime traffic monitoring, anomaly detection, and autonomous navigation. Despite promising advancements, real-world deployment faces critical challenges such as data scarcity, domain shift, multimodal data fusion, and explainability. This special session aims to bring together researchers and practitioners to discuss recent developments, share challenges, and explore emerging opportunities in applying deep learning to maritime problems. The call for ideas invites academics and practitioners to submit proposals for  maritime applications of deep learning techniques: challenges and opportunities.

This special session focuses on the intersection of deep learning techniques and maritime applications, addressing both theoretical advances and practical deployments. Topics of interest include but are not limited to: 

•  Deep learning techniques for vessel detection and classification in satellite and drone imagery  

• Anomaly detection in maritime traffic using spatiotemporal data  

• Autonomous navigation and path planning for vessels using reinforcement learning and imitation learning techniques 

• Sensor fusion and multimodal learning techniques for maritime environments  

• Handling imbalanced, limited, and noisy maritime datasets  

• Explainable AI (XAI) and trustworthy deep learning techniques in safety-critical maritime systems  

• Domain adaptation and generalization for maritime environments  

• Real-time deep learning solutions for maritime surveillance 

The session encourages submissions from academia, industry, and governmental bodies addressing real-world challenges, datasets, and solutions. 

 Journal Publication:  A selected set of top-quality papers may be invited to submit full papers to a special issue.

Best Paper: All the regular papers will be considered for the BEST PAPER AWARD 

The maritime domain is rapidly adopting deep learning techniques for diverse applications, including vessel detection, maritime traffic monitoring, anomaly detection, and autonomous navigation. Despite promising advancements, real-world deployment faces critical challenges such as data scarcity, domain shift, multimodal data fusion, and explainability. This special session aims to bring together researchers and practitioners to discuss recent developments, share challenges, and explore emerging opportunities in applying deep learning to maritime problems. The call for ideas invites academics and practitioners to submit proposals for  maritime applications of deep learning techniques: challenges and opportunities.

This special session focuses on the intersection of deep learning techniques and maritime applications, addressing both theoretical advances and practical deployments. Topics of interest include but are not limited to: 

•  Deep learning techniques for vessel detection and classification in satellite and drone imagery  

• Anomaly detection in maritime traffic using spatiotemporal data  

• Autonomous navigation and path planning for vessels using reinforcement learning and imitation learning techniques 

• Sensor fusion and multimodal learning techniques for maritime environments  

• Handling imbalanced, limited, and noisy maritime datasets  

• Explainable AI (XAI) and trustworthy deep learning techniques in safety-critical maritime systems  

• Domain adaptation and generalization for maritime environments  

• Real-time deep learning solutions for maritime surveillance 

The session encourages submissions from academia, industry, and governmental bodies addressing real-world challenges, datasets, and solutions. 

 Journal Publication:  A selected set of top-quality papers may be invited to submit full papers to a special issue.

Best Paper: All the regular papers will be considered for the BEST PAPER AWARD 

The maritime domain is rapidly adopting deep learning techniques for diverse applications, including vessel detection, maritime traffic monitoring, anomaly detection, and autonomous navigation. Despite promising advancements, real-world deployment faces critical challenges such as data scarcity, domain shift, multimodal data fusion, and explainability. This special session aims to bring together researchers and practitioners to discuss recent developments, share challenges, and explore emerging opportunities in applying deep learning to maritime problems. The call for ideas invites academics and practitioners to submit proposals for  maritime applications of deep learning techniques: challenges and opportunities.

This special session focuses on the intersection of deep learning techniques and maritime applications, addressing both theoretical advances and practical deployments. Topics of interest include but are not limited to: 

•  Deep learning techniques for vessel detection and classification in satellite and drone imagery  

• Anomaly detection in maritime traffic using spatiotemporal data  

• Autonomous navigation and path planning for vessels using reinforcement learning and imitation learning techniques 

• Sensor fusion and multimodal learning techniques for maritime environments  

• Handling imbalanced, limited, and noisy maritime datasets  

• Explainable AI (XAI) and trustworthy deep learning techniques in safety-critical maritime systems  

• Domain adaptation and generalization for maritime environments  

• Real-time deep learning solutions for maritime surveillance 

The session encourages submissions from academia, industry, and governmental bodies addressing real-world challenges, datasets, and solutions. 

 Journal Publication:  A selected set of top-quality papers may be invited to submit full papers to a special issue.

Best Paper: All the regular papers will be considered for the BEST PAPER AWARD