AI-Driven Marine Vessel Detection Through Satellite Imagery:  A Deep Learning Approach

Author(s)	Abizer Jesawada, Harsh Singh, Kavita Patel, Dipti Kumari, Rohini Bhosale
Country	India
Abstract	This study explores an advanced methodology for detecting marine vessels via satellite imagery, utilizing a deep learning framework tailored for maritime surveillance. A novel convolutional neural network (CNN) architecture, optimized for varying vessel sizes and adverse conditions, achieved a detection accuracy of 94%, significantly surpassing traditional computer vision techniques. The approach integrates innovative preprocessing techniques and a robust post-processing framework to ensure reliability under challenging scenarios like partial cloud cover and rough sea states. This work demonstrates the potential of AI-driven solutions for enhancing real-world maritime operations, including national security and traffic management.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-29
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.34231
Short DOI	https://doi.org/g8xgmc

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International Journal For Multidisciplinary Research