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Ship Classification in SAR Images via Densely Connected Triplet CNNs Integrating Fisher Discrimination Regularized Metric Learning

Year: 2025

Type: article

Abstract: This paper focuses on ship classification from Synthetic Aperture Radar (SAR) images using a Triplet Convolutional Neural Network (CNN) integrated with Fisher Discrimination Regularized Metric Learning. The system involves dataset creation, triplet sampling, model training, and ship type prediction (Cargo, Passenger, Dredging, Tanker). A GUI built with Tkinter allows users to upload SAR images and view the prediction results.

Source: International Journal of Science and Research (IJSR)

DOI: 10.21275/sr25416204849

Authors: Rayna Elsa Mathai, Sindhu Daniel

Language: English

Topic: Advanced SAR Imaging Techniques

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4409679323

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