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Revolutionizing SAR Image Interpretation on Cutting-Edge Approaches for Ship Detection and Beyond

Revolutionizing SAR Image Interpretation on Cutting-Edge Approaches for Ship Detection and Beyond
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Author(s): R. Regin (SRM Institute of Science and Technology, Ramapuram, India), K. Lalith Reddy (SRM Institute of Science and Technology, Ramapuram, India), R. Sanjay Narayanan (SRM Institute of Science and Technology, Ramapuram, India), Y. Likhith Srinivas (SRM Institute of Science and Technology, Ramapuram, India), R. Steffi (Vins Christian College of Engineering, India), S. Saranya (Dhaanish Ahmed College of Engineering, India)and S. R. Saranya (Dhaanish Ahmed College of Engineering, India)
Copyright: 2026
Pages: 26
Source title: Pioneering AI and Data Technologies for Next-Gen Security, IoT, and Smart Ecosystems
Source Author(s)/Editor(s): Ferdin Joe John Joseph (Thai-Nichi Institute of Technology, Thailand), Karthikeyan Chinnusamy (Veritas, USA), Joseph Jeganathan (University of Bahrain, Bahrain), Ahmed J. Obaid (University of Kufa, Iraq)and S. Suman Rajest (Dhaanish Ahmed College of Engineering, India)
DOI: 10.4018/979-8-3373-4672-4.ch005

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Abstract

SAR photography has great potential for remote sensing, especially ship identification. This study discusses revolutionary SAR picture interpretation advances, including ship recognition methods and uses beyond maritime surveillance. We explain SAR technology and ship identification issues such as clutter, noise, and environmental variability. We suggest novel solutions using machine learning and signal processing advances. We investigate CNNs, RNNs, and deep learning architectures for robust ship detection in SAR images. We also study adaptive filtering and wavelet transforms to improve detection accuracy and eliminate false alarms. SAR picture interpretation has applications beyond ship detection, as this study discusses. These include disaster management, environmental monitoring, and maritime security, demonstrating SAR technology's versatility in meeting varied social needs. Sentinel-1 and TerraSAR-X are public SAR image interpretation datasets that inform our analysis.

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