To Enhance maritime safety using advanced deep learning techniques, particularly CNNs, to accurately identify and classify ships in satellite and surveillance images. The maritime industry’s critical role in global trade demands more sophisticated technologies to ensure safety, security, and efficient navigation. The ship identification system’s applications are diverse, including classifying cargo vessels, tankers, fishing boats, and distinguishing legitimate ships from potential threats. Real time monitoring capabilities facilitate proactive responses to emergencies and security risks. The expected findings and results of the project indicate successful object identification in the environment contributes to a safer and more secure maritime environment by leveraging deep learning and CNNs for ship classification and identification. By enabling real-time monitoring and integration into surveillance systems, the system enhances maritime safety, facilitating efficient and secure global trade and navigation.


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    Title :

    Enhancing Maritime Safety with Deep Learning for Ship Identification


    Additional title:

    Lect.Notes Social.Inform.


    Contributors:

    Conference:

    International Conference on Broadband Communications, Networks and Systems ; 2024 ; Hyderabad, India February 16, 2024 - February 17, 2024



    Publication date :

    2025-02-07


    Size :

    4 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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