Ship Detection in Medium-Resolution SAR Images using Deep learning

International Journal of Electronics and Communication Engineering

© 2021 by SSRG - IJECE Journal

Volume 8 Issue 5

Year of Publication : 2021

Authors : M.Muruga Lakshmi, Dr.S.Thayammal

10.14445/23488549/IJECE-V8I5P101

How to Cite?

M.Muruga Lakshmi, Dr.S.Thayammal, "Ship Detection in Medium-Resolution SAR Images using Deep learning," SSRG International Journal of Electronics and Communication Engineering, vol. 8,  no. 5, pp. 1-5, 2021. Crossref, https://doi.org/10.14445/23488549/IJECE-V8I5P101

Abstract:

Due to its noticeable advantages of working, Synthetic aperture radar (SAR) has become a significant device for many remote sensing applications. The Existing methods for SAR images perform well under some constraints. In this work, a ship detection method based on CNN (Convolutional Neural Network) called VGG net (Visual Geometry Group) is proposed. To improve the performance of ship detection by adopting multi-level features produced by the convolution layers, which fits ships with different sizes. The Simulation results of the proposed method are compared with the existing method

Keywords:

Synthetic aperture radar, Convolutional Neural Network.

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